{"title":"Products","description":null,"products":[{"product_id":"fujitsu-palmsecure-f-pro-mouse","title":"Fujitsu PalmSecure F-Pro Mouse","description":"\u003ch3\u003ePalm Vein Authentication System \n\u003c\/h3\u003e\n\u003ch4\u003eFeatures\u003c\/h4\u003e\n\u003cul style=\"margin-left: 40px;\"\u003e\n\t\u003cli\u003eContactless authentication is hygienic and non-invasive \u003c\/li\u003e\n\t\u003cli\u003eAdvanced authentication algorithm produces a high level of accuracy with an FAR (false accept rate) of 0.00001% @ a FRR (false reject rate) of 1.0% \u003c\/li\u003e\n\t\u003cli\u003eStandard USB 2.0 connectivity \u003c\/li\u003e\n\t\u003cli\u003ePalm vein biometric logon for Microsoft Winlogon and centralized administration \u003c\/li\u003e\n\t\u003cli\u003eCompatible with Microsoft Active Directory and Novell eDirectory\u003c\/li\u003e\n\t\u003cli\u003eFast and easy enrollment (under one minute)\u003c\/li\u003e\n\t\u003cli\u003eEncrypted repository for template storage\u003c\/li\u003e\n\t\u003cli\u003eEnterprise level event logging capability\u003c\/li\u003e\n\t\u003cli\u003eNo Residual Trace Technology – No biometric footprint left behind after authentication Biometric Products\u003c\/li\u003e\n\u003c\/ul\u003e\u003cbr\u003e\n\u003cp\u003e\nThe Fujitsu PalmSecure Mouse device is a highly reliable, non-invasive and easy to use biometric authentication mechanism that seamlessly integrates into your login security and access management environments.\n\u003c\/p\u003e\n\u003cp\u003e\n\t\u003cb\u003eFast, Easy and Accurate User Authentication\u003c\/b\u003e\u003cbr\u003e\n\tQuickly gaining access to data is critical in many of today's work environments. While deployment of the PalmSecure mouse will help protect against fraudulent access to sensitve information, it also enables an immediate and convenient authentication process for users.\n\u003c\/p\u003e\n\u003cp\u003e\n\t\u003cb\u003eHow It Works\u003c\/b\u003e\u003cbr\u003e\n\tSimply place your palm 2 inches above the PalmSecure mouse scanner and within a second the device captures a near-infrared image of your unique palm vein pattern. The Fujitsu advanced algorithm converts this image into a digitized biometric template and matches it against a database of pre-registered templates. The algorithm will determine whether the comparison of templates results in a match to confirm the identity.\n\u003c\/p\u003e\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003ctable style=\"width: 70%;\" cellspacing=\"2\" cellpadding=\"2\" border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr valign=\"top\"\u003e\n\t\u003ctd style=\"font-weight: bold;\" width=\"40%\" bgcolor=\"f4f4f4\"\u003e\n\t\tWeight\n\t\u003c\/td\u003e\n\t\u003ctd width=\"60%\" bgcolor=\"#FFFFFF\"\u003e\n\t\tca 80 g\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\t\u003ctd style=\"font-weight: bold;\" width=\"40%\" bgcolor=\"f4f4f4\"\u003e\n\t\tDimensions\n\t\u003c\/td\u003e\n\t\u003ctd width=\"60%\" bgcolor=\"#FFFFFF\"\u003e\n \t50 x 90 x 26 mm\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\t\u003ctd style=\"font-weight: bold;\" width=\"40%\" bgcolor=\"f4f4f4\"\u003e\n\t\tTechnical specification\n\t\u003c\/td\u003e\n\t\u003ctd width=\"60%\" bgcolor=\"#FFFFFF\"\u003e\n\t\tMid size mouse with integrated PalmSecure sensor, 3 button 1 wheel USB 1 m cable, Laser sensor 1000 dpi\n\t\t\u003cbr\u003e Lighting environment for authentication:\u003cbr\u003e\n\t\t\u003cul\u003e\n\t\t\t\u003cli\u003eEnrollment: below 1700 lux (halogenlamp) and below 5000 lux natural light\u003c\/li\u003e\n\t\t\t\u003cli\u003eVerification: below 45000 lux normal mode and below 80000 lux in high power mode\u003c\/li\u003e\n\t\t\u003c\/ul\u003e\n\t\tEncrypting scheme: AES (lenght of cryptography key more than 128 bit)\n\t\t\u003cbr\u003eAuthentication rate: FFR x‹ 0,01% FAR below 0,00001%\u003cbr\u003e Template compatible with OEM sensor (M1E) from V30 library and higher in I format \u003cbr\u003eAuthentication time (verify) x‹ 1 sec, This product cannot be used under direct sunlight\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\t\u003ctd style=\"font-weight: bold;\" width=\"40%\" bgcolor=\"f4f4f4\"\u003e\n\t\tFeatures and functions\n\t\u003c\/td\u003e\n\t\u003ctd width=\"60%\" bgcolor=\"#FFFFFF\"\u003e\n\t\tHighly secure biometric solution through palm vein authentication. It provides a powerful combination of strong biometric authentication for log-in security, access management and data protection for both client and enterprise environments.\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\t\u003ctd style=\"font-weight: bold;\" width=\"40%\" bgcolor=\"f4f4f4\"\u003e\n\t\tSupported operating systems\n\t\u003c\/td\u003e\n\t\u003ctd width=\"60%\" bgcolor=\"#FFFFFF\"\u003e\n\t\tWindows 7, Windows 8, Windows 10\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\n","brand":"Fujitsu","offers":[{"title":"Default Title","offer_id":40901736202342,"sku":"102431","price":287.22,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/f-pro-min.jpg?v=1711046820"},{"product_id":"fujitsu-palmsecure-f-pro","title":"Fujitsu PalmSecure F-Pro","description":"\u003ch3\u003eYour Small and Fast Biometric Choice for Universal Registration\u003c\/h3\u003e\n\u003ch4\u003eFeatures\u003c\/h4\u003e\n\u003cul style=\"margin-left: 40px;\"\u003e\n\u003cli\u003ePalm vein biometric authentication\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eExposure times are reduced which shortens the capture time, preventing blurring while capturing palm\u003c\/li\u003e\n\u003cli\u003eFrame rate is increased to capture a slowly moving palm\u003c\/li\u003e\n\u003cli\u003eStandard USB connection (\u003cb\u003e2 meter cable included\u003c\/b\u003e)\u003c\/li\u003e\n\u003cli\u003eImproved tolerance under ambient sunlight\u003c\/li\u003e\n\u003cli\u003ePalmSecure technology has never failed to successfully enroll a user\u003c\/li\u003e\n\u003cli\u003eF-Pro sensor 30% smaller than legacy sensors\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003eThe Fujitsu PalmSecure F-Pro palm vein scanner is highly reliable, and the best-of-breed biometric authentication using Fujitsu’s award-winning PalmSecure technology.\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eFast, Small and Accurate User Authentication\u003c\/b\u003e\u003cbr\u003eQuickly register and authenticate users to provide access to mission-critical data in various industry verticals. The F-Pro sensor is 30% smaller and faster than legacy systems, and has been enhanced to more quickly capture templates while supporting a wider range of ambient temperature and sunlight.\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eHow It Works\u003c\/b\u003e\u003cbr\u003eSimply place your palm 2 inches above the sensor and a template and the device captures a near-infrared image of your unique palm vein pattern will be captured and encrypted in under 1 second. A Fujitsu algorithm coverts this image into an encrypted biometric template that can be matched against a database of pre-registered templates. The algorithm will determine whether the comparison of templates results in a match to confirm the identity.\u003c\/p\u003e\n\u003cp\u003eThe F-Pro sensor is the ideal desktop device to replace passwords and prevent the use of shared, stolen or faked ID credentials in logical access applications such as employee network access (single sign-on), bank teller authentication, patient and healthcare provider authentication, and point of sale (POS) transactions.\u003c\/p\u003e\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003ctable bgcolor=\"#FFFFFF\" border=\"1\" cellpadding=\"2\" cellspacing=\"2\" style=\"width: 70%;\"\u003e\n\u003ctbody\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eReading system\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eReading by near-infrared light\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eScope of capture\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eEntire palm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eCapturing distance\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003e40 to 60mm (Enrollment) \u003cbr\u003e35 to 70mm (Authentication)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eDimensions\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eWidth 29 x Depth 29 x Height 13mm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eWeight\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eBelow 12 g\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eVoltage of Power supply\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003e4.4 to 5.4 V\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eCurrent consumption\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003e500 mA (Max at normal-power mode) 900 mA (Max at high-power mode)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003ePower saving mode\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003e50 mA (Max)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003ePower consumption\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003e2.5 W (Max at normal-power mode) \u003cbr\u003e4.5 W (Max at high-power mode)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003ePower source\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eProvided by the USB Interface cable\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eHost interface\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eCable Length included 1 m \u003cbr\u003eMax length supported is 4 m\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eInterface connector\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eSeries \"Micro-B\" plug (with 5 pins)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eInstallation angle\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eFull direction\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eTemperature\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003e-40 to 85 degrees Celsius\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eHumidity\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003e20 to 90%RH\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eMaterial of the surface of Sensor unit\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eGlass\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eEncryption method\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eAES (Length of cryptography key more than 128 bit)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eAuthentication rate\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eFRR: 1.00% (no retry) \u003cbr\u003eFAR: Below 0.00001%\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eElectro magnetic wave standard\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eVCCI ClassB, FCC ClassB, EN ClassB\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eSafety Standard\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eUL60950-1, EN60950-1\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eEnvironmental Regulation\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eConforms to RoHS and WEEE\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eWarranty\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003e1 Year\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e","brand":"Fujitsu","offers":[{"title":"Fujitsu PalmSecure F-Pro with no cable","offer_id":40901736235110,"sku":"102432","price":263.15,"currency_code":"GBP","in_stock":true},{"title":"Fujitsu PalmSecure F-Pro \u0026 USB 2.0 cable 6.5' (2m)","offer_id":40901736267878,"sku":"102432","price":277.15,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/f-pro.jpg?v=1711046822"},{"product_id":"fujitsu-f-pro-mouse-guide","title":"Fujitsu F-Pro Mouse Guide","description":"\u003cp\u003eThe PalmSecure F-Pro Mouse Guide provides users with a simple solution for ensuring correct placement of the hand above the PalmSecure F-Pro Mouse.\u003c\/p\u003e","brand":"Fujitsu","offers":[{"title":"Default Title","offer_id":40901736300646,"sku":"102439","price":28.21,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/fpro-shield-min.jpg?v=1711046824"},{"product_id":"fujitsu-palmsecure-f-pro-palm-vein-scanner-u-guide-bundle","title":"Fujitsu PalmSecure F-Pro Palm Vein Scanner + U-Guide Bundle","description":"\u003cp\u003e\u003cb\u003eIncluded: PalmSecure F-Pro Palm Vein Scanner, U-Guide \u0026amp; detachable USB cable\u003c\/b\u003e\u003c\/p\u003e\n\u003ch3\u003eYour Small and Fast Biometric Choice for Universal Registration\u003c\/h3\u003e\n\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ch4\u003eFeatures\u003c\/h4\u003e\n\u003cul style=\"margin-left: 40px;\"\u003e\n\u003cli\u003ePalm vein biometric authentication\u003cbr\u003e\n\u003c\/li\u003e\n\u003cli\u003eExposure times are reduced which shortens the capture time, preventing blurring while capturing palm\u003c\/li\u003e\n\u003cli\u003eFrame rate is increased to capture a slowly moving palm\u003c\/li\u003e\n\u003cli\u003eStandard USB connection (\u003cb\u003e2 meter cable included\u003c\/b\u003e)\u003c\/li\u003e\n\u003cli\u003eImproved tolerance under ambient sunlight\u003c\/li\u003e\n\u003cli\u003ePalmSecure technology has never failed to successfully enroll a user\u003c\/li\u003e\n\u003cli\u003eF-Pro sensor 30% smaller than legacy sensors\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003cp\u003eThe Fujitsu PalmSecure F-Pro palm vein scanner is highly reliable, and the best-of-breed biometric authentication using Fujitsu’s award-winning PalmSecure technology.\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eFast, Small and Accurate User Authentication\u003c\/b\u003e\u003cbr\u003eQuickly register and authenticate users to provide access to mission-critical data in various industry verticals. The F-Pro sensor is 30% smaller and faster than legacy systems, and has been enhanced to more quickly capture templates while supporting a wider range of ambient temperature and sunlight.\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eHow It Works\u003c\/b\u003e\u003cbr\u003eSimply place your palm 2 inches above the sensor and a template and the device captures a near-infrared image of your unique palm vein pattern will be captured and encrypted in under 1 second. A Fujitsu algorithm coverts this image into an encrypted biometric template that can be matched against a database of pre-registered templates. The algorithm will determine whether the comparison of templates results in a match to confirm the identity.\u003c\/p\u003e\n\u003cp\u003eThe F-Pro sensor is the ideal desktop device to replace passwords and prevent the use of shared, stolen or faked ID credentials in logical access applications such as employee network access (single sign-on), bank teller authentication, patient and healthcare provider authentication, and point of sale (POS) transactions.\u003c\/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003ctable bgcolor=\"#FFFFFF\" border=\"1\" cellpadding=\"2\" cellspacing=\"2\" style=\"width: 70%;\"\u003e\n\u003ctbody\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eReading system\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eReading by near-infrared light\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eScope of capture\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eEntire palm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eCapturing distance\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003e40 to 60mm (Enrollment) \u003cbr\u003e35 to 70mm (Authentication)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eDimensions\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eWidth 29 x Depth 29 x Height 13mm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eWeight\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eBelow 12 g\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eVoltage of Power supply\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003e4.4 to 5.4 V\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eCurrent consumption\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003e500 mA (Max at normal-power mode) 900 mA (Max at high-power mode)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003ePower saving mode\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003e50 mA (Max)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003ePower consumption\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003e2.5 W (Max at normal-power mode) \u003cbr\u003e4.5 W (Max at high-power mode)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003ePower source\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eProvided by the USB Interface cable\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eHost interface\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eCable Length included 1 m \u003cbr\u003eMax length supported is 4 m\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"40%\" style=\"font-weight: bold;\"\u003eInterface connector\u003c\/td\u003e\n\u003ctd width=\"60%\"\u003eSeries \"Micro-B\" plug (with 5 pins)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"top\"\u003e\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e","brand":"Fujitsu","offers":[{"title":"Linux","offer_id":40901736333414,"sku":"102435","price":302.82,"currency_code":"GBP","in_stock":true},{"title":"Windows","offer_id":40901736366182,"sku":"102435","price":302.82,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/handguide-combo-min.jpg?v=1711046826"},{"product_id":"cmitech-emx-30","title":"CMITech EMX-30 Dual Iris Scanner","description":"\u003ch3\u003e\u003cspan style=\"caret-color: #000000; color: #000000; font-family: Tahoma, sans-serif; font-size: 14.666667px; font-style: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: auto; text-align: left; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration: none; display: inline !important; float: none;\" data-mce-style=\"caret-color: #000000; color: #000000; font-family: Tahoma, sans-serif; font-size: 14.666667px; font-style: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: auto; text-align: left; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration: none; display: inline !important; float: none;\" data-mce-fragment=\"1\"\u003eNON-RETURNABLE\/NON-REFUNDABLE\u003c\/span\u003e\u003c\/h3\u003e\n\u003cp\u003e\u003cstrong\u003eThis product is EOL. Quantities are very limited.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eThe CMITech EMX-30 is a USB tethered dual eye iris biometrics imaging device that quickly captures highest quality iris biometric images. Easy to use, the system’s simple and intuitive user interface makes positioning fast and repeatable, even for subjects with little or no acclimation. The advanced image capture and processing architecture offers the fastest iris biometric capture speeds in the industry.\u003c\/p\u003e\n\u003cp\u003eOperating at a range of 32 to 35 cm, the EMX-30 is fully hands-free and contactless. The exclusive face-finding functionality locates each subject’s position and automatically tilts the imager head to adjust for subject height. This functionality is optical, which allows the EMX-30 to be placed behind an optical glass or plastic window, making it ideal for placement behind an environmental shield.\u003c\/p\u003e\n\u003cp\u003eDeveloped with the latest in system design technologies by one of the leaders in the industry, the EMX-30 is physically robust, highly reliable and durable. It is configured as a USB tethered device, making the EMX-30 highly cost effective. \u003cbr\u003eNOTE: The EMX-30 does not come with the desktop base. Please add the option above to your order.\u003c\/p\u003e\n\u003ch2\u003eCMITech EMX-30 Features\u003c\/h2\u003e\n\u003cul style=\"margin-left: 40px;\"\u003e\n\u003cli\u003e\u003cspan style=\"background-color: initial;\"\u003eState-of-the-art optical design\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"background-color: initial;\"\u003eAdvanced, proprietary stereoscopic eye localization\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"background-color: initial;\"\u003eSimple and repeatable subject user interface\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"background-color: initial;\"\u003eSimples of user instructions\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"background-color: initial;\"\u003eProprietary optics for positioning indicators eliminate parallax viewing problems \u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"background-color: initial;\"\u003eAutomatic vertical height adjustment\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"background-color: initial;\"\u003eStand-off distance of 32 to 35 mm\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"background-color: initial;\"\u003eLarge depth of capture of 30 mm\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"background-color: initial;\"\u003eHigh speed, simultaneous dual sensors\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"background-color: initial;\"\u003eNear-real time off-axis gaze detection\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"background-color: initial;\"\u003eMotion detection\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"background-color: initial;\"\u003eFace image capture\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"background-color: initial;\"\u003eVery wide interpupillary distance range of 45 to 85 mm\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"background-color: initial;\"\u003eCompact, lightweight design\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"background-color: initial;\"\u003eModule version for integration into kiosks or other enclosures \u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"background-color: initial;\"\u003eOptional Extended Depth of Capture to 6.0 cm (new)\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003ctable style=\"width: 70%;\" class=\"data\" cellspacing=\"2\" cellpadding=\"2\" border=\"1\" bgcolor=\"#FFFFFF\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eDimensions\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e219 x 161 x 58 mm (8.6 x 6.3 x 2.3 inches) \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eImage output \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eMeets ISO 19794-6; exceeds 4.0 Ip\/mm @ \u0026gt;60% contrast \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eIris diameter \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e240 pixels for average 11.5 diameter iris (200 to 285 pixels for full range of 9.5 to 13.5 mm diameter irises) \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eIris image pixel resolution \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e640 x 480 pixels, 8 bits. Supports multiple formats \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eOperational iris imaging distance \u003cbr\u003e(stand-off range)\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e315 to 345 mm (12.4 to 13.6 inches) in Normal mode \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eDepth of field \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e30 mm (1.2 inches) \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eInter-pupillary distance covered \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e45 to 85 mm (1.8 to 3.4 inches) \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eTime of capture \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eAbout 0.5 second, typical, from time subject’s eyes are placed within capture volume \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eIR illumination for iris imaging \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eDual LED: wavelengths of 850 nm nominal (about 50%); and 750 nm nominal (about 50%) \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eMaximum user positioning speed \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e125 mm per second (4.9 inches per sec.) in “Z direction” \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e","brand":"CMITech","offers":[{"title":"CMITech EMX-30","offer_id":40901736398950,"sku":"102162","price":1592.25,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/1200Iris_Scanner_EMX-30_-min-sw.jpg?v=1711046829"},{"product_id":"fs50-fips201-piv-compliant-usb-2-0-two-finger-scanner","title":"FS50 FIPS201\/PIV Compliant USB 2.0 Two Finger Scanner","description":"\u003cp\u003eFS50 is a professional Fingerprint Scanner from Futronic with 1.6 x 1.5 inch (40.64 x 38.10 mm) scanning area. Its advanced optical system can capture a high quality image in 0.1 second. It can also handle bad fingers such as dry, wet, blurred and scarred without any problem. Its scanning window is crown glass prism with a thickness of 33mm. There is also special anti-scratching coating on the scanning surface of the prism. This makes FS50 even more robust and ensures long term heavy duty usage in any harsh environment.\u003c\/p\u003e\n\u003cp\u003eFS50 FIPS201\/PIV can capture single finger, dual finger and roll finger image. It was certified by FBI to be compliant with PIV-071006 Image Quality Specification for Single Finger Reader. So FS50 meets the US Federal Information Processing Standard 201(FIPS 201) for Personal Identification Verification (PIV) of Federal Employees and Contractors. It is also listed in the US General Services Administration (GSA) FIPS 201 Evaluation Program Approved Product List.\u003c\/p\u003e\n\u003cp\u003eA unique serial number is factory-programmed into the USB Device Descriptor of each FS50. So every FS50 is traceable and this is very important for government identity management projects.\u003c\/p\u003e\n\u003ch4\u003eHave a question or need more information? Tell us about it and our personnel will respond shortly.\u003c\/h4\u003e\n\u003ch2\u003eFutronic FS50 FIPS201\/PIV USB 2.0 Features\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eFIPS 201 and PIV compliant\u003c\/strong\u003e certified by FBI and included in US General Services Administration approved products list.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eLarge platen area\u003c\/strong\u003e allows to scan 1 or 2 flat fingerprints simultaneously, or 1 rolled fingerprint.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003ePrecise optics\u003c\/strong\u003e allow to scan almost undistorted fingerprint image.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eInfra-red illumination\u003c\/strong\u003e allows to scan wet, dry, blurred, scarred and other problematic fingers.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRugged sensor\u003c\/strong\u003e thick (33 mm) crown glass prism used for platen.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003ctable bgcolor=\"#FFFFFF\" border=\"\" cellpadding=\"\" cellspacing=\"\" width:=\"\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" width=\"\" class=\"\" font-weight:=\"\"\u003eScanner Name\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eFS50 FIPS201\/PIV Compliant USB 2.0 Two Finger Scanner\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\"\u003eManufacturer\u003c\/td\u003e\n\u003ctd text-align:=\"\"\u003eFutronic Technology Co. Ltd.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\"\u003eConnection\u003c\/td\u003e\n\u003ctd text-align:=\"\"\u003eUSB 2.0\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\"\u003eManufacturer Supported OS\u003c\/td\u003e\n\u003ctd\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cspan font-size:=\"\"\u003eWindows XP\/2003, 32 bit and 64 bit. \u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan font-size:=\"\"\u003eWindows Vista\/2008, 32 bit and 64 bit. \u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan font-size:=\"\"\u003eWindows 7\/8, 32 bit and 64 bit. \u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan font-size:=\"\"\u003eLinux with kernel 2.4 or higher (for both x86 and ARM9) \u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan font-size:=\"\"\u003eWindows CE 5.0 and 6.0 (for both x86 and ARM9) \u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" font-weight:=\"\" vertical-align:=\"\"\u003eNeurotechnology Supported OS \u003csup\u003e(1)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003ctd\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cspan font-size:=\"\"\u003eMicrosoft Windows (32bit and 64bit) \u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan font-size:=\"\"\u003eLinux (32bit)\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\"\u003eResolution\u003c\/td\u003e\n\u003ctd text-align:=\"\"\u003e500 dpi\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" text-align:=\"\"\u003e\n\u003cspan font-weight:=\"\"\u003eFingerprint Capture Method \u003c\/span\u003e\u003cbr\u003e\n\u003c\/td\u003e\n\u003ctd text-align:=\"\"\u003eRoll or Touch\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\"\u003eImage capture area (Platen size)\u003c\/td\u003e\n\u003ctd text-align:=\"\"\u003e41 x 38 mm (1.6\"\" x 1.5\"\")\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\"\u003eFingerprint image size\u003c\/td\u003e\n\u003ctd text-align:=\"\"\u003e800 x 750 pixels\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\"\u003eSensor type\u003c\/td\u003e\n\u003ctd text-align:=\"\"\u003eOptical, CMOS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\"\u003eIllumination\u003c\/td\u003e\n\u003ctd text-align:=\"\"\u003eInfrared LEDs\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\"\u003eDevice size\u003c\/td\u003e\n\u003ctd text-align:=\"\"\u003e110 x 110 x 45 mm (4.3\"\" x 4.3\"\" x 1.8\"\")\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\"\u003eDevice weight\u003c\/td\u003e\n\u003ctd text-align:=\"\"\u003e380 grams (0.8 lbs) without USB cable\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\"\u003eOperating temperature\u003c\/td\u003e\n\u003ctd text-align:=\"\"\u003e-10°C ~ +55°C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp\u003e\u003csup\u003e(1)\u003c\/sup\u003e These operating systems are supported by Neurotechnology SDKs.\u003c\/p\u003e\n\u003ch2\u003e\u003cstrong\u003eElectrical characteristics\u003c\/strong\u003e\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eESD contact - 8KV and air discharge - 16KV, no permanent damage\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eStandards Compliance\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eFIPS 201 and PIV compliant\u003c\/strong\u003e certified by FBI and included in US General Services Administration approved products list.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eProduct Compatibility\u003c\/h2\u003e\n\u003cp\u003eThe Futronic FS50 FIPS201\/PIV USB 2.0 Reader is compatible with many different software development kits and applications. Below is the list of products that are currently known to support this scanner. Please note that some applications and development kits require specific versions of the drivers to be installed. Please contact us if you need additional information.\u003c\/p\u003e\n\u003ch3\u003eSupported Software Development Kits:\u003c\/h3\u003e\n\u003cp\u003eVeriFinger Standard and Extended SDK\u003c\/p\u003e\n\u003cp\u003eMegaMatcher Standard and Extended SDK\u003c\/p\u003e\n\u003ch3\u003eSupported Applications:\u003c\/h3\u003e\n\u003cp\u003eFbF \u003csup\u003e(TM)\u003c\/sup\u003e Device Listener\u003c\/p\u003e","brand":"Futronic Technology Co.","offers":[{"title":"Default Title","offer_id":40901736759398,"sku":"101117","price":160.03,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/101117-2-min.jpg?v=1711046831"},{"product_id":"crossmatch-u-are-u-5300-fips-201-piv-fap-30-certified-usb-fingerprint-reader","title":"HID DigitalPersona 5300 FIPS 201\/PIV, FAP 30 Certified USB Fingerprint Reader","description":"\u003cp\u003eThe HID DigitalPersona 5300 is a compact optical single fingerprint reader meeting both FIPS 201\/PIV and FBI Mobile ID FAP 30 standards. The reader is designed to meet the high volume requirements of large-scale Civil ID and commercial enrollment and authentication applications. Incorporating a durable IP64 rated glass platen that is also highly resistant to chemical and physical damage, the HID DigitalPersona 5300 is well suited for harsh environments.\u003c\/p\u003e\n\u003cp\u003eThe reader rapidly captures and produces fingerprint images at 500 ppi resolution in ANSI and ISO\/IEC standard formats. On-board electronics automatically control calibration and data transfer over the USB interface. The HID DigitalPersona 5300 can be used with any standards-compatible fingerprint template extractor or matcher, including the DigitalPersona FingerJet MINEX-certified Biometric Engine. The HID DigitalPersona 5300 and the FingerJet Biometric Engine provide an unmatched ability to authenticate even the most difficult fingerprints accurately and rapidly.\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eApplications\u003c\/b\u003e\u003cbr\u003eEnrollment and authentication for:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eVoter registration\u003c\/li\u003e\n\u003cli\u003eNational ID\u003c\/li\u003e\n\u003cli\u003eBenefits entitlement\u003c\/li\u003e\n\u003cli\u003eMicro finance and healthcare\u003c\/li\u003e\n\u003cli\u003eNetwork and application access\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eFeatures\u003c\/b\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eFIPS 201\/PIV certified\u003c\/li\u003e\n\u003cli\u003eMobile ID FAP 30 certified\u003c\/li\u003e\n\u003cli\u003e500 ppi images\u003c\/li\u003e\n\u003cli\u003eCompact size\u003c\/li\u003e\n\u003cli\u003eCounterfeit finger rejection\u003c\/li\u003e\n\u003cli\u003eCompatible with U.are.U SDKs\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eKey Specifications\u003c\/b\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003ePixel resolution: 500dpi\u003c\/li\u003e\n\u003cli\u003e8-bit grayscale (256 gray levels)\u003c\/li\u003e\n\u003cli\u003eScan capture area: 20.32 mm x 25.4 mm\u003c\/li\u003e\n\u003cli\u003eReader size: 86mm L x 53mm W x 31mm H (+\/-0.5mm)\u003c\/li\u003e\n\u003cli\u003eUSB 2.0 (High Speed)\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003ctable bgcolor=\"#FFFFFF\" border=\"\" cellpadding=\"\" cellspacing=\"\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\"\u003eSupply Voltage\u003c\/td\u003e\n\u003ctd width=\"\"\u003e5.0V ±5%\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\"\u003eSupply Current scanning\u003c\/td\u003e\n\u003ctd\u003e150 mA (Typical)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\"\u003eSupply Current idle mode\u003c\/td\u003e\n\u003ctd\u003e\u0026lt; 40 mA (Typical)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\"\u003eSupply Current suspend mode\u003c\/td\u003e\n\u003ctd\u003e\u0026lt; 0.5 mA (Maximum)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\"\u003eTemperature, Operating\u003c\/td\u003e\n\u003ctd\u003e-10 - 50 C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\"\u003eHumidity, Operating\u003c\/td\u003e\n\u003ctd\u003e0% - 90% non-condensing\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\"\u003eTemperature, Storage\u003c\/td\u003e\n\u003ctd\u003e-20 - 55 C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\"\u003eHumidity, Storage\u003c\/td\u003e\n\u003ctd\u003e0% - 90% non-condensing\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\"\u003eScan Data\u003c\/td\u003e\n\u003ctd\u003e8-bit grayscale\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\"\u003eTop Surface\u003c\/td\u003e\n\u003ctd\u003eIP64-rated seal between top case and glass surface*\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\"\u003eInterface\u003c\/td\u003e\n\u003ctd\u003eUSB 2.0 High Speed\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\"\u003eWeight\u003c\/td\u003e\n\u003ctd\u003e245 grams\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\"\u003eStandards Compliance\u003c\/td\u003e\n\u003ctd\u003eFIPS 201 PIV, Mobile ID FAP 30, RoHS, UL, USB, WEEE\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\"\u003eESD\u003c\/td\u003e\n\u003ctd\u003eIEC61000-4-2 Level 4\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003cp\u003e*IP64 rating is for the seal between the top case and the glass imaging window. Devices containing the embedded module must seal the module top case to their chassis or housing to extend the IP64 protection to the device.\u003c\/p\u003e","brand":"DigitalPersona","offers":[{"title":"Default Title","offer_id":40901736792166,"sku":"101107","price":136.97,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/101107-2-min.jpg?v=1711046833"},{"product_id":"biometrika-hiscan-pro-optical-fingerprint-scanner","title":"Biometrika HiScan-Pro Optical Fingerprint Scanner","description":"\u003cp\u003eHiScan-Pro, an improved version of the HiScan PIV, is a professional fingerprint scanner (1\"\"x1\"\"), compliant with IAFIS Appendix F Image Quality Specifications for 500DPI fingerprint scanners, that are more stringent than PIV specifications. HiScan-PRO has been conceived to become the reference in the single-finger scanner market: the high quality optical design makes HiScan-PRO the ideal solution for applications requiring a high level accuracy and interoperability with international standards (e.g. forensic and civil AFIS, border control, electronic passport, visa, identity card, etc).\u003c\/p\u003e\n\n\u003cp\u003eHiScan-Pro can be used as a simple device for acquiring high quality fingerprint images or, in combination with the Biometrika FxISO SDK engine, to create complete biometric solutions for fingerprint-based identity verification or identification.\u003c\/p\u003e\n\n\n\u003ch2\u003eBiometrika HiScan Pro Features\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eImproved version of HiScan\u003c\/li\u003e\n\u003cli\u003eIAFIS-IQS certified\u003c\/li\u003e\n\u003cli\u003eCapable of 500 and 1000dpi\u003c\/li\u003e\n\u003cli\u003eNative resolution of 1000dpi\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\n\n\n\n\u003ctable class=\"data\" style=\"font-size: 14px; width: 729px;\" cellspacing=\"2\" cellpadding=\"2\" border=\"1\" bgcolor=\"#FFFFFF\"\u003e\n   \u003ctbody\u003e\n      \u003ctr\u003e\n         \u003ctd class=\"cap_left\" style=\"width: 281px; font-weight: bold;\" bgcolor=\"f4f4f4\"\u003eDevice name\u003c\/td\u003e\n         \u003ctd width=\"60%\"\u003eBiometrika HiScan Pro Fingerprint Scanner\u003cbr\u003e\n\u003c\/td\u003e\n      \u003c\/tr\u003e\n      \u003ctr\u003e\n         \u003ctd class=\"cap_left\" style=\"font-weight: bold;\" bgcolor=\"f4f4f4\"\u003eManufacturer\u003c\/td\u003e\n         \u003ctd\u003e Biometrika srl. \u003c\/td\u003e\n      \u003c\/tr\u003e\n      \u003ctr\u003e\n         \u003ctd class=\"cap_left\" style=\"font-weight: bold;\" bgcolor=\"f4f4f4\"\u003eDevice connection\u003c\/td\u003e\n         \u003ctd\u003eUSB 2.0\u003c\/td\u003e\n      \u003c\/tr\u003e\n      \u003ctr\u003e\n         \u003ctd class=\"cap_left\" style=\"font-weight: bold;\" bgcolor=\"f4f4f4\"\u003eNeurotechnology Supported OS (1)\u003c\/td\u003e\n         \u003ctd\u003eMicrosoft Windows 10 only\u003cbr\u003e\n\u003c\/td\u003e\n      \u003c\/tr\u003e\n      \u003ctr\u003e\n         \u003ctd class=\"cap_left\" style=\"font-weight: bold;\" bgcolor=\"f4f4f4\"\u003eManufacturer Supported OS \u003c\/td\u003e\n         \u003ctd\u003eMicrosoft Windows 10 only\u003cbr\u003e\n\u003c\/td\u003e\n      \u003c\/tr\u003e\n      \u003ctr\u003e\n         \u003ctd class=\"cap_left\" style=\"font-weight: bold;\" bgcolor=\"f4f4f4\"\u003eSensor resolution\u003c\/td\u003e\n         \u003ctd\u003e1000 dpi\u003c\/td\u003e\n      \u003c\/tr\u003e\n      \u003ctr\u003e\n         \u003ctd class=\"cap_left\" style=\"font-weight: bold;\" bgcolor=\"f4f4f4\"\u003eImage capture area (Platen size)\u003c\/td\u003e\n         \u003ctd\u003e25.4 x 25.4 mm (1.0\" x 1.0\")\u003c\/td\u003e\n      \u003c\/tr\u003e\n      \u003ctr\u003e\n         \u003ctd class=\"cap_left\" style=\"font-weight: bold;\" bgcolor=\"f4f4f4\"\u003eSensor type\u003c\/td\u003e\n         \u003ctd\u003eOptical\u003c\/td\u003e\n      \u003c\/tr\u003e\n      \u003ctr\u003e\n         \u003ctd class=\"cap_left\" style=\"font-weight: bold;\" bgcolor=\"f4f4f4\"\u003eDevice size\u003c\/td\u003e\n         \u003ctd\u003e122 x 73 x 61 mm (4.8\" x 2.9\" x 2.4\")\u003c\/td\u003e\n      \u003c\/tr\u003e\n      \u003ctr\u003e\n         \u003ctd\u003e\n\u003cspan style=\"font-weight: bold;\" bgcolor=\"f4f4f4\"\u003eTemperature Range\u003c\/span\u003e\u003cbr\u003e\n\u003c\/td\u003e\n         \u003ctd\u003e5°C - 45°C\u003c\/td\u003e\n      \u003c\/tr\u003e\n      \u003ctr\u003e\n         \u003ctd\u003e\n\u003cspan style=\"font-weight: bold;\" bgcolor=\"f4f4f4\"\u003eHumidity Range\u003c\/span\u003e\u003cbr\u003e\n\u003c\/td\u003e\n         \u003ctd\u003e0-90% (not condensing)\u003c\/td\u003e\n      \u003c\/tr\u003e\n   \u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003cp\u003e(1) These operating systems are supported by Neurotechnology SDKs. \u003cbr\u003eDevice manufacturers may have different lists of supported operating systems.\u003c\/p\u003e\n","brand":"Biometrika srl","offers":[{"title":"Default Title","offer_id":40901737218150,"sku":"101206","price":344.78,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/101202-2-min_27495493-5700-4319-b59d-1c7dac0f866f.jpg?v=1711046838"},{"product_id":"cmitech-bmt-20-dual-iris-scanner","title":"CMITech BMT-20 Dual Iris Scanner","description":"\u003cp\u003eThe CMITech BMT-20 is a binoculars-type iris biometrics\nimaging device that quickly captures highest quality iris biometric images.\nExceeding industry standards for image quality, this system optimizes matching\naccuracy, essential in very large scale deployments for which de-duplication is\na core deliverable. Easy to use, the system can be reliably positioned by the\nsubject with minimal instructions, or by an operator with the aid of\npositioning feedback LEDs on the top of the imager's housing.\u003c\/p\u003e\n\n\u003cp\u003eThe patentpending optical design of the BMT-20 includes\nexpanded depth of field and a very large interpupillary distance range,\nproviding effortless capture for subjects of all ages. Intended for\napplications in which subjects have limited prior experience with biometrics\ndevices, the BMT-20 is ideal for enrollment programs of all sizes, including\nthose involving very young children. Designed with the latest in optical and\nsystem control technology by one of the leaders in the industry, the BMT-20 is\nphysically robust, highly reliable and durable.\u003c\/p\u003e\n\n\u003cp\u003eThis system meets the elevated IP64 intrusion protection\nstandard and is sealed against dust and other airborne particles to provide\nextended life in harsh environmental conditions. CMITech's products and\ntechnology are leading the industry in cost effective and easy to use iris\nrecognition solutions serving the full range of identification and\nauthentication use cases, including physical and logical access control,\nnational identity, law enforcement, border crossing and immigration control\n    applications.\u003c\/p\u003e\n\n\n\u003ch2\u003eCMITech BMT-20\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cspan style=\"\" background-color: initial\u003eState-of-the-art-optical design\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"\" background-color: initial\u003eSingle sensor design\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"\" background-color: initial\u003eLong internal optical path\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"\" background-color: initial\u003eDedicated, on-board image processor supports very\nhigh speed, simultaneous capture of subject's irises\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"\" background-color: initial\u003eExtended depth of field\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"\" background-color: initial\u003eWide inter-pupillary distance tolerance\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"\" background-color: initial\u003eAll solid-state design-no moving parts\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"\" background-color: initial\u003eMeets IP64-6 specifications for particulate\nintrusion prevention\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"\" background-color: initial\u003eNear-real time off-axis gaze detection\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"\" background-color: initial\u003eInternal white LED\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"\" background-color: initial\u003eMotion detection\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"\" background-color: initial\u003eFoldable side visors and forehead positioning rest\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"\" background-color: initial\u003eExternal color LED positioning indicators\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"\" background-color: initial\u003ePosition sensor\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"\" background-color: initial\u003eHigh temperature range\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan style=\"\" background-color: initial\u003ePowered by USB 2.0 cable\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003ctable style=\"\" class=\"\" data cellspacing=\"\" cellpadding=\"\" border=\"\" bgcolor=\"ffffff\" width:=\"\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\t\u003ctd bgcolor=\"f4f4f4\"\u003e\n\t\t\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003eDimensions\u003c\/span\u003e\n\t\u003c\/td\u003e\n\t\u003ctd\u003e\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003e210\nx 161 x 58 mm (8.6 x 6.3 x 2.3 inches)\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd bgcolor=\"f4f4f4\"\u003e\n\t\t\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003eImage\noutput\n\t\t\u003c\/span\u003e\n\t\u003c\/td\u003e\n\t\u003ctd\u003e\n\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003eMeets\nor exceeds ISO 19794-6\u003c\/span\u003e\u003cp class=\"\" msolistparagraph style=\"\" text-indent:-.25in level1 lfo1\u003e\n\t\t\t\u003c\/p\u003e\n\u003cp\u003e\u003c\/p\u003e\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003eMTF\/spatial\nresolution\u003c\/span\u003e\u003c\/td\u003e\n\t\u003ctd\u003e\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003eExceeds\n4.0 Ip\/mm @ \u0026gt; 60% contrast\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd bgcolor=\"f4f4f4\"\u003e\n\t\t\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003eIris\nimage pixel resolution\n\t\t\u003c\/span\u003e\n\t\u003c\/td\u003e\n\t\u003ctd\u003e\n\t\t\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003e640\nx 480 pixels, 8 bits. Supports multiple formats\n\t\t\u003c\/span\u003e\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd bgcolor=\"f4f4f4\"\u003e\n\t\t\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003eOperational path distance\u003c\/span\u003e\n\u003c\/td\u003e\n\t\u003ctd\u003e\n\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003e350\nto 380 mm\u003c\/span\u003e\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd bgcolor=\"f4f4f4\"\u003e\n\t\t\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003eDepth\nof field\n\t\t\u003c\/span\u003e\n\t\u003c\/td\u003e\n\t\u003ctd\u003e\n\t\t\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003e30 mm (1.2 inches)\u003c\/span\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd bgcolor=\"f4f4f4\"\u003e\n\t\t\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003eInter-pupillary\ndistance covered\n\t\t\u003c\/span\u003e\n\t\u003c\/td\u003e\n\t\u003ctd\u003e\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003e40\nto 90 mm (1.6 to 3.5 inches)\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd bgcolor=\"f4f4f4\"\u003e\n\t\t\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003eTime\nof capture\n\t\t\u003c\/span\u003e\n\t\u003c\/td\u003e\n\t\u003ctd\u003e\n\t\t\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003eAbout\n1.0 second, from time of head placement\u003c\/span\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd bgcolor=\"f4f4f4\"\u003e\n\t\t\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003eIR\nillumination for iris imaging\n\t\t\u003c\/span\u003e\n\t\u003c\/td\u003e\n\t\u003ctd\u003e\n\t\t\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003eDual\nLED: wavelengths of 850 nm nominal (about 50%); and 750 nm nominal (about 50%)\n\t\t\u003c\/span\u003e\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003eInternal\nLED for pupil contraction\u003c\/span\u003e\u003c\/td\u003e\n\t\u003ctd\u003e\u003cspan style=\"\" font-size: font-family: calibri sans-serif\u003eBroadband\nvisible (white)\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e","brand":"CMITech","offers":[{"title":"Default Title","offer_id":40901737250918,"sku":"102165","price":512.34,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/102165-2-min.jpg?v=1711046840"},{"product_id":"fujitsu-f-pro-standard-hand-guide","title":"Fujitsu F-Pro Standard Hand Guide","description":"\u003cp\u003eThe PalmSecure F-Pro Standard Hand Guide provides users with a simple solution for ensuring exact placement of the hand above the PalmSecure F-Pro Standard Sensor. The sensor snaps securely into the bottom of the Standard Guide. Sits securely on a desktop or counter top and can be fastened down if needed.\u003c\/p\u003e\n","brand":"Fujitsu","offers":[{"title":"Default Title","offer_id":40901737283686,"sku":"102438","price":8.26,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/102438-2-min.jpg?v=1711046842"},{"product_id":"livescan-software-for-applicant","title":"Applicant Live Scan Solution","description":"","brand":"Fulcrum Biometrics, Inc","offers":[{"title":"Default Title","offer_id":40901737316454,"sku":null,"price":0.0,"currency_code":"GBP","in_stock":true}]},{"product_id":"criminal-live-scan-solution-page","title":"Criminal Live Scan Solution","description":"","brand":"Fulcrum Biometrics, Inc","offers":[{"title":"Default Title","offer_id":40901737349222,"sku":null,"price":0.0,"currency_code":"GBP","in_stock":true}]},{"product_id":"digitalpersona-u-are-u-4500","title":"HID DigitalPersona 4500","description":"\u003cp\u003eThe \u003cspan\u003eHID DigitalPersona 4500 \u003c\/span\u003eFingerprint Reader is a USB device built on the latest optical fingerprint reader technology. Easy to install and use; the many benefits of fingerprint biometrics start here. Its compact and attractive design conserves desk space in enterprises, its professional modern appearance looks elegant in point-of-service environments, and its ability to read a fingerprint from any angle makes it ideal for applications where users share PCs.\u003c\/p\u003e\n\u003cp\u003eThe \u003cspan\u003eHID DigitalPersona 4500\u003c\/span\u003e Reader is a USB fingerprint reader featuring a sleek design with a soft, cool blue glow and, of course, the unsurpassed performance DigitalPersona is known for. Made for power-users and shared environments, the 4500 is the natural choice for those that want and need the very best.\u003c\/p\u003e\n\u003ch2\u003e\n\u003cspan\u003eHID DigitalPersona 4500\u003c\/span\u003e Features\u003c\/h2\u003e\n\u003cp\u003eHere’s a look at just some of its features and benefits: \u003cbr\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ctable border=\"1\" cellpadding=\"2\" cellspacing=\"2\" id=\"standard_table\" style=\"width: 95%;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"text-align: left; width: 25%; vertical-align: top;\" class=\"space_right space_bottom rule_top\"\u003e\u003cstrong\u003eBlue LED\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd align=\"left\" valign=\"top\" width=\"70%\" class=\"space_bottom rule_top\"\u003eSoft, cool blue glow fits into any environment. Provides a pleasing presence; doesn't compete in low light environments, such as restaurants, or conflict with alarm condition colors, such as in healthcare.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\" valign=\"top\" class=\"space_right space_bottom rule_top\"\u003e\u003cstrong\u003eSmall form factor\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd align=\"left\" valign=\"top\" class=\"space_bottom rule_top\"\u003eConserves valuable desk space.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\" valign=\"top\" class=\"space_right space_bottom rule_top\"\u003e\u003cstrong\u003eRugged construction\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd align=\"left\" valign=\"top\" class=\"space_bottom rule_top\"\u003eHigh-quality metal casing weighted to resist unintentional movement.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\" valign=\"top\" class=\"space_right space_bottom rule_top\"\u003e\u003cstrong\u003eSpecial undercoating\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd align=\"left\" valign=\"top\" class=\"space_bottom rule_top\"\u003eStays where you put it because of a special undercoating.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\" valign=\"top\" class=\"space_right space_bottom rule_top\"\u003e\u003cstrong\u003eRotation invariant\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd align=\"left\" valign=\"top\" class=\"space_bottom rule_top\"\u003eTouch it from any direction, it still provides a high quality image and matching performance, perfect for shared environments.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\" valign=\"top\" class=\"space_right space_bottom rule_top\"\u003e\u003cstrong\u003eExcellent image quality\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd align=\"left\" valign=\"top\" class=\"space_bottom rule_top\"\u003eHigh-quality optics ensure best image every time.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\" valign=\"top\" class=\"space_right space_bottom rule_top\"\u003e\u003cstrong\u003eWorks well with dry, moist, or rough fingerprints\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd align=\"left\" valign=\"top\" class=\"space_bottom rule_top\"\u003eReliable performance over the widest population of users. Reads even the most difficult fingerprints.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003ctable bgcolor=\"ffffff\" border=\"1\" cellpadding=\"2\" cellspacing=\"2\" class=\"data\" style=\"width: 70%;\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" style=\"width: 40%; font-weight: bold;\" class=\"cap_left\"\u003eDevice name\u003c\/td\u003e\n\u003ctd width=\"60%\" style=\"text-align: left;\"\u003e\n\u003cspan\u003eHID DigitalPersona 4500 \u003c\/span\u003eReader\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"cap_left\" style=\"font-weight: bold;\"\u003eManufacturer\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e\u003ca href=\"http:\/\/www.digitalpersona.com\/\" title=\"Open DigitalPersona web site\" target=\"_blank\"\u003eDigitalPersona, Inc.\u003c\/a\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"cap_left\" style=\"font-weight: bold;\"\u003eDevice connection\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003eUSB 2.0\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"cap_left\" style=\"font-weight: bold;\"\u003eSupported OS \u003csup\u003e(1)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003eMicrosoft Windows (32-bit and 64-bit)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"cap_left\" style=\"font-weight: bold;\"\u003eSensor resolution\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e512 dpi\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"cap_left\" style=\"font-weight: bold;\"\u003eImage capture area (Platen size)\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e15 x 18 mm (0.6\" x 0.7\")\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"cap_left\" style=\"font-weight: bold;\"\u003eSensor type\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003eOptical\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"cap_left\" style=\"font-weight: bold;\"\u003eIllumination\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003eBlue LEDs\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"cap_left\" style=\"font-weight: bold;\"\u003eDevice size\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e65 x 36 x 16 mm (2.6\" x 1.4\" x 0.6\")\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"cap_left\" style=\"font-weight: bold;\"\u003eOperating temperature\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e0°C ~ +40°C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"cap_left\" style=\"font-weight: bold;\"\u003eOperating humidity\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e20-80 % (non-condensing)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp\u003e(1) These operating systems are supported by Neurotechnology SDKs. \u003cbr\u003eDevice manufacturers may have different lists of supported operating systems. \u003cbr\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ch2\u003eProduct Compatibility\u003c\/h2\u003e\n\u003cp\u003eThe \u003cspan\u003eHID DigitalPersona 4500\u003c\/span\u003e Reader is compatible with many different software development kits and applications. Below is the list of products that are currently known to support this scanner. Please note that some applications and development kits require specific versions of the drivers to be installed. Please contact us if you need additional information. \u003cspan style=\"font-weight: bold;\"\u003e\u003cbr\u003e\u003c\/span\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ch3\u003eSupported Software Development Kits:\u003c\/h3\u003e\n\u003cp\u003eVeriFinger Standard and Extended SDK \u003cbr\u003eMegaMatcher Standard and Extended SDK\u003cbr\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ch3\u003eSupported Applications:\u003c\/h3\u003e\n\u003cp\u003eFbF Device Listener \u003cbr\u003eScan \u0026amp; Pin\u003c\/p\u003e","brand":"DigitalPersona","offers":[{"title":"Default Title","offer_id":40901737381990,"sku":"101102","price":101.96,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/101102-sl-1-min.jpg?v=1711046845"},{"product_id":"eikontouch-tc710-fingerprint-sensor","title":"HID EikonTouch TC710 Fingerprint Sensor","description":"\u003cp\u003eThe HID EikonTouch® TC710 USB capacitive fingerprint reader provides quick and reliable biometric authentication. The HID EikonTouch® TC710 uses patented technology to capture fine print details. The result is the ability to capture a wide range of fingerprints with superior image quality for a broad range of use cases.\u003c\/p\u003e\n\u003cp\u003eThe first and most widely deployed, FIPS 201 PIV certified silicon fingerprint reader provides on board processing for image capture and template generation, matching and storage. This reader also protects sensitive data to and from the device using encryption up to AES-256.\u003c\/p\u003e\n\u003cp\u003eThe HID EikonTouch® TC710 fingerprint reader is a USB peripheral perfect for individual desk-top users. Utilizing the same proven compact design as our HID DigitalPersona® 4500 optical fingerprint reader the TC710 conserves desk space with a professional, modern housing design. This form factor works well in a wide range of vertical markets including government, healthcare and other logical access control applications. Superior accuracy and usability are a result of the improved finger guide ergonomics and the LED which is located just above the sensor to provide user feedback during the biometric capture and matching process. The TC710 housing is IP65 rated to protect against dust and moisture penetration. This capability supports device cleaning including up to 70% isopropyl alcohol.\u003c\/p\u003e\n\u003cp\u003eThe DigitalPersona® Biometric Software Developer Kit (SDK) provides flexible APIs to enable fast integration of the HID EikonTouch® TC710 into a broad range of applications.\u003c\/p\u003e\n\u003cp\u003eWhether you are an enterprise customer or a system integrator, our biometric identity verification solutions provide a natural extension to your security systems and applications.\u003c\/p\u003e\n\u003ch2\u003eApplications\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eDesktop PC security\u003c\/li\u003e\n\u003cli\u003eMobile PC security\u003c\/li\u003e\n\u003cli\u003eEPCS \u0026amp; healthcare applications\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eFeatures\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eFIPS 201 PIV certified image quality\u003c\/li\u003e\n\u003cli\u003eOn device processing for template generation, matching and storage\u003c\/li\u003e\n\u003cli\u003eWorks well with dry, moist or rough fingerprints\u003c\/li\u003e\n\u003cli\u003eEncrypted USB communication\u003c\/li\u003e\n\u003cli\u003ePAD (Presentation Attack Detection)\u003c\/li\u003e\n\u003cli\u003eMultiple USB connectors and cable lengths\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eApplications\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eDesktop PC security\u003c\/li\u003e\n\u003cli\u003eMobile PC security\u003c\/li\u003e\n\u003cli\u003eEPCS \u0026amp; healthcare applications\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003ctable style=\"width: 70%;\" class=\"data\" cellspacing=\"2\" cellpadding=\"2\" border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"width: 40%;\"\u003eProduct Name\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\" width=\"60%\"\u003eHID EikonTouch TC710 Capacitive Fingerprint Reader\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" bgcolor=\"f4f4f4\"\u003eCOMPACT FORM FACTOR\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eFingerprint Sensor\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003eTCS1C (touch)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003ePackage Size (mm)\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e35 x 63.5 x 14.2\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eScanned Finger Area (mm)\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e12.8 x 18\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003ePixel Array Size (pixels)\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e256 x 360\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eWeight\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e124\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eForm Factor\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003eSame housing as the DigitalPersona 4500 optical fingerprint reader with weighted base for added stability.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eCable \u0026amp; Connector Options\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003eCable lengths: 20 or 183 cm (7.8 or 72 in.) lengths USB Connectors: Type-A, Micro-B or Type-C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" bgcolor=\"f4f4f4\"\u003eHIGH PERFORMANCE\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eAcquisition Speed\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e5.5 frames\/sec\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eImage Resolution\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e508 dpi\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eGrayscale Image Depth\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e8-bit (256 levels)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eInterface\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003eUSB 2.0 full speed\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" bgcolor=\"f4f4f4\"\u003eSECURE\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eUSB Data Encryption\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e5Up to AES-256\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eOn-board Data Storage\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003eUp to 100 finger templates\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" bgcolor=\"f4f4f4\"\u003eRUGGEDIZED\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eESD Protection\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003eIEC 61000-4-2 level 4: 15 kV air, 8 kV contact\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eIngress Protection\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003eIP65 for moisture and dust protection\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eOperating Temperature\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e-10° to 50° C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eProtective Coating\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e\u0026gt; 2 million touches\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eHumidity\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e\u0026gt; 5% to 95% RH\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eCertification\u003c\/td\u003e\n\u003ctd style=\"text-align: left;\"\u003e\u0026gt; CE\/FCC\/WHQL \/UL\/RoHS\/Reach\/WEEE\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003ch2\u003eProduct Compatibility\u003c\/h2\u003e\n\u003cp\u003eThe HID EikonTouch TC710 Fingerprint Reader is compatible with many different software development kits and applications. Below is the list of products that are currently known to support this scanner. Please note that some applications and development kits require specific versions of the drivers to be installed. Please contact us if you need additional information.\u003c\/p\u003e\n\u003ch3\u003eSupported Software Development Kits:\u003c\/h3\u003e\n\u003cp\u003eVeriFinger Standard and Extended SDK \u003cbr\u003eMegaMatcher Standard and Extended SDK\u003c\/p\u003e","brand":"HID Global","offers":[{"title":"Default Title","offer_id":40901737414758,"sku":"101145-01","price":109.43,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/eikon.jpg?v=1711046847"},{"product_id":"fingerprint-matcher-license","title":"Fingerprint Matcher License","description":"\u003cp\u003e\n\tThe Fingerprint Matcher performs fingerprint template matching \nin 1-to-1 (verification) and 1-to-many (identification) modes. \n\t\t\t\t\t\t\t\t\tAlso the Fingerprint Matcher component includes \n\t\u003cstrong\u003efused\u003c\/strong\u003e matching algorithm that allows to increase template matching reliability by:\n\u003c\/p\u003e\n\u003cul\u003e\n\t\u003cli\u003ematching templates that contain 2 or more fingerprint records (note that Fingerprint Segmenter or Fingerprint Client components are required to perform template extraction from images that contain more than one fingerprint);\u003c\/li\u003e\n\t\u003cli\u003ematching templates that contain fingerprint, face, \nvoiceprint and\/or iris records (note that matching faces, irises and \nvoiceprints requires to purchase \n\tFace Matcher, Iris Matcher and Voice Matcher components correspondingly).\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\n\t\t\t\t\t\t\t\t\tThe Fingerprint Matcher component matches \n\t\u003cstrong\u003e40,000 fingerprints per second\u003c\/strong\u003e and is designed to be used in \u003cstrong\u003edesktop\u003c\/strong\u003e or mobile biometric systems, which run on PCs or laptops with at least Intel \u003cstrong\u003eCore 2 Q9400\u003c\/strong\u003e (2.67 GHz) processor.\n\u003c\/p\u003e\n\u003cp\u003e\n\t\t\t\t\t\t\t\t\tOne Fingerprint Matcher license is included with VeriFinger Standard SDK, VeriFinger Extended SDK, MegaMatcher Standard SDK\n and MegaMatcher Extended SDK.\n\t\t\t\t\t\t\t\t\tMore licenses for this component can be purchased any time by \nVeriFinger SDK and MegaMatcher SDK customers.\n\u003c\/p\u003e\n","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":40901737447526,"sku":"100219","price":20.65,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo_c2934596-f549-4f35-a825-dbd674c3fe6f.jpg?v=1711046849"},{"product_id":"fast-fingerprint-matcher-license","title":"Fast Fingerprint Matcher License","description":"\u003cp\u003e\n\tThe Fast Fingerprint Matcher component is intended for the\nlarge-scale AFIS and biometric systems. The component includes a \n\t\u003cstrong\u003efast\nmatching mode\n\t\u003c\/strong\u003e and also has the same matching mode as the\nregular \nFingerprint\nMatcher.\n\u003c\/p\u003e\n\n\u003cp\u003e\n\tMulti-biometric fused template matching can be achieved by combining\nthe Fast Fingerprint Matcher component with Face and\/or Iris Matchers\n(regular or fast versions of them can be used depending on project\nimplementation).\n\u003c\/p\u003e\n\u003cp\u003e\n\tSee the reliability and performance testing results on the MegaMatcher\nStandard and MegaMatcher\nExtended SDK Techical Specs tab for the comparison of matching\nmodes and multi-modal template matching.\n\u003c\/p\u003e\n\u003cp\u003e\n\tOne Fast Fingerprint Matcher license is included with MegaMatcher Standard SDK. Two Fast Fingerprint Matcher licenses are included\nwith MegaMatcher Extended SDK. More licenses for this component can\nbe purchased any time by MegaMatcher SDK customers.\n\u003c\/p\u003e\n","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":40901737480294,"sku":"100220","price":456.12,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo200523-2-min_c16f616a-9037-4b78-94ed-dd3647d6810f.jpg?v=1711046851"},{"product_id":"fingerprint-image-processing","title":"Fingerprint Image Processing","description":"\u003cp\u003eThe Fingerprint Image Processing component creates fingerprint templates from fingerprint images and is designed to be used in high-volume server applications, which run on server hardware with at least dual Intel Xeon Gold 6126 (2.6 GHz) processors. The component performs template extraction at a speed of 3,000 fingerprints per minute.\u003c\/p\u003e\n\u003cp\u003eProprietary image quality control may be applied to accept only good quality fingerprint images.\u003c\/p\u003e\n\u003cp\u003eThe component can generalize a fingerprint template from several images that contain the same fingerprint to improve the template's quality.\u003c\/p\u003e\n\u003cp\u003eThe fingerprint image segmentation module is used to separate fingerprints if an image contains more than one fingerprint. This functionality enables the component to process fingerprints from scanned tenprint card or image captured using scanners that allow to scan two or more fingers at once.\u003c\/p\u003e\n\u003cp\u003eFingerprint pattern classification module is included with the component to determine a fingerprint pattern class. The classification is usually used in forensics, but it also may be used to increase fingerprint matching speed. The defined classes are:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eLeft Slant Loop;\u003c\/li\u003e\n\u003cli\u003eRight Slant Loop;\u003c\/li\u003e\n\u003cli\u003eTented Arch;\u003c\/li\u003e\n\u003cli\u003eWhorl;\u003c\/li\u003e\n\u003cli\u003eScar;\u003c\/li\u003e\n\u003cli\u003e\"Unknown\" – for the nondetermined classes.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003cp\u003eThe Fingerprint Image Processing component allows to integrate support for fingerprint template and image format standards with new or existing biometric systems based on MegaMatcher SDK.\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eNeurotechnology proprietary fingerprint template format\u003c\/li\u003e\n\u003cli\u003eBioAPI 2.0 (ISO\/IEC 19784-1:2006) (Framework and Biometric Service Provider for fingerprint identification engine)\u003c\/li\u003e\n\u003cli\u003eCBEFF V1.2 (ANSI INCITS 398-2008) (Common Biometric Exchange Formats Framework)\u003c\/li\u003e\n\u003cli\u003eCBEFF V2.0 (ISO\/IEC 19785-1:2006 with Amd. 1:2010, 19785-3:2007 with Amd. 1:2010) (Common Biometric Exchange Formats Framework)\u003c\/li\u003e\n\u003cli\u003eCBEFF V3.0 (ISO\/IEC 19785-3:2015) (Common Biometric Exchange Formats Framework)\u003c\/li\u003e\n\u003cli\u003eISO\/IEC 19794-2:2005 with Cor. 1:2009 (Biometric Data Interchange Formats – Finger Minutiae Data (General Record and On-Card Formats)\u003c\/li\u003e\n\u003cli\u003eISO\/IEC 19794-2:2011 with Cor. 1:2012 (General Record and On-Card Formats) and Amd.2:2015 (XML encoding and clarification of defects)\u003c\/li\u003e\n\u003cli\u003eISO\/IEC 19794-4:2005 with Cor. 1:2011 (Biometric Data Interchange Formats - Finger Image Data)\u003c\/li\u003e\n\u003cli\u003eISO\/IEC 19794-4:2011 with Cor. 1:2012 (Biometric Data Interchange Formats - Finger Image Data)\u003c\/li\u003e\n\u003cli\u003eISO\/IEC 29794-1:2016 (Biometric sample quality)\u003c\/li\u003e\n\u003cli\u003eANSI\/INCITS 378-2004 (Finger Minutiae Format for Data Interchange)\u003c\/li\u003e\n\u003cli\u003eANSI\/INCITS 378-2009 with Amd. 1:2010 (Finger Minutiae Format for Data Interchange)\u003c\/li\u003e\n\u003cli\u003eANSI\/INCITS 381-2004 (Finger Image-Based Data Interchange Format)\u003c\/li\u003e\n\u003cli\u003eANSI\/INCITS 381-2009 with Amd. 1:2011 (Finger Image-Based Data Interchange Format)\u003c\/li\u003e\n\u003cli\u003eANSI\/NIST-CSL 1-1993 (Data Format for the Interchange of Fingerprint, Facial, \u0026amp; SMT Information)\u003c\/li\u003e\n\u003cli\u003eANSI\/NIST-ITL 1a-1997 (Data Format for the Interchange of Fingerprint, Facial, \u0026amp; SMT Information)\u003c\/li\u003e\n\u003cli\u003eANSI\/NIST-ITL 1-2000 (Data Format for the Interchange of Fingerprint, Facial, \u0026amp; SMT Information)\u003c\/li\u003e\n\u003cli\u003eANSI\/NIST-ITL 1-2007 (Data Format for the Interchange of Fingerprint, Facial, \u0026amp; Other Biometric Information)\u003c\/li\u003e\n\u003cli\u003eANSI\/NIST-ITL 1a-2009 (Data Format for the Interchange of Fingerprint, Facial, \u0026amp; Other Biometric Information)\u003c\/li\u003e\n\u003cli\u003eANSI\/NIST-ITL 1-2011 (Data Format for the Interchange of Fingerprint, Facial, \u0026amp; Other Biometric Information)\u003c\/li\u003e\n\u003cli\u003eANSI\/NIST-ITL 1-2011 Update:2013 Edition 2 (Data Format for the Interchange of Fingerprint, Facial, \u0026amp; Other Biometric Information)\u003c\/li\u003e\n\u003cli\u003eANSI\/NIST-ITL 1-2011 Update:2015 (Data Format for the Interchange of Fingerprint, Facial, \u0026amp; Other Biometric Information)\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003cp\u003eThe component allows conversion between Neurotechnology proprietary fingerprint templates, ISO\/IEC 19794-2:2005, ISO\/IEC 19794-2:2011, ANSI\/INCITS 378-2004, ANSI\/INCITS 378-2009 and ANSI\/NIST-ITL templates.\u003c\/p\u003e\n\u003cp\u003eThe Fingerprint Image Processing component also includes advanced image formats support modules:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eJPEG 2000 image format support module with 1000 ppi Fingerprint Profile;\u003c\/li\u003e\n\u003cli\u003eNIST IHead image format support module;\u003c\/li\u003e\n\u003cli\u003emodule with NIST Fingerprint Image Quality (NFIQ) algorithm, a standard method to determine fingerprint image quality.\u003c\/li\u003e\n\u003cli\u003eWSQ (Wavelet Scalar Quantization) image format module allows to compress a fingerprint image up to 10-15 times, as well as read images in this format. WSQ compression process is \"lossy\", meaning that the reconstructed image is not equal to the original (some information is lost). However, the WSQ algorithm was specially designed to minimize the loss of fingerprint information therefore the reconstructed image is as close as possible to the original.\u003cbr\u003e Neurotechnology's implementation of WSQ 3.1 fingerprint image compression was certified by the FBI as compliant with the accuracy requirements in the Wavelet Scalar Quantization (WSQ) Gray-Scale Fingerprint Image Compression Specification, Version 3.1.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003eFor 50 licenses or more, contact Fulcrum Biometrics.\u003c\/p\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":40901737513062,"sku":"100230","price":1689.35,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo4.jpg?v=1711046853"},{"product_id":"face-client-license","title":"Face Client License","description":"\u003cp\u003e\n\tThe Face Client component is a combination of the Face Extractor, Face Token Image and Face BSS components.\n\t\t\t\t\t\t\t\t\tIt is designed for the systems that need to support all functionality of the mentioned components on the same PC.\n\t\t\t\t\t\t\t\t\tUsing these licenses allows to optimize component license costs as well as reduce license management.\n\u003c\/p\u003e\n\u003cp\u003e\n\t\t\t\t\t\t\t\t\tThe Face Client extracts a single face template in \n\t\u003cstrong\u003e0.6 seconds\u003c\/strong\u003e.\n\t\t\t\t\t\t\t\t\tThe specified performance requires a \n\t\u003cstrong\u003ePC or laptop\u003c\/strong\u003e with at least Intel \u003cstrong\u003eCore 2 Q9400\u003c\/strong\u003e (2.67 GHz) processor.\n\u003c\/p\u003e\n\u003cp\u003e\n\t\t\t\t\t\t\t\t\tThree non-concurrent licenses and one concurrent license for \nthe Face Client component are included with VeriLook 5.5 Extended SDK, \nMegaMatcher 5.0 Standard SDK and MegaMatcher 5.0 Extended SDK.\n\t\t\t\t\t\t\t\t\tMore non-concurrent and concurrent licenses for this component \ncan be purchased any time by VeriLook 5.5 Extended SDK customers and \nMegaMatcher 5.0 SDK customers.\n\u003c\/p\u003e\n","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":40901737578598,"sku":"100310-2","price":49.58,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo_43440ae8-d8f9-418d-8d18-b2670925e0b1.jpg?v=1711046855"},{"product_id":"biometric-sso-iam","title":"Biometric SSO \u0026 IAM","description":"","brand":"Fulcrum Biometrics, Inc","offers":[{"title":"Default Title","offer_id":40901737611366,"sku":null,"price":0.0,"currency_code":"GBP","in_stock":true}]},{"product_id":"face-matcher-license","title":"Face Matcher License","description":"\n\u003cp\u003eThe Face Matcher performs facial template matching in 1-to-1 (verification) and 1-to-many (identification) modes. Also the Face Matcher component includes fused matching algorithm that allows to increase template matching reliability by matching templates that contain fingerprint, face, voiceprint and\/or iris records (note that matching fingerprints, irises and voiceprints requires to purchase Fingerprint Matcher, Iris Matcher and Voice Matcher components correspondingly).\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eThe Face Matcher component matches \u003c\/span\u003e\u003cstrong\u003e40,000 faces per second\u003c\/strong\u003e\u003cspan\u003e and is designed to be used in \u003c\/span\u003e\u003cstrong\u003edesktop\u003c\/strong\u003e\u003cspan\u003e or mobile biometric systems, which run on PCs or laptops with at least Intel \u003c\/span\u003e\u003cstrong\u003eCore 2 Q9400\u003c\/strong\u003e\u003cspan\u003e (2.67 GHz) processor.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eOne Face Matcher license is included with VeriLook Standard SDK, VeriLook Extended SDK, MegaMatcher Standard SDK and MegaMatcher Extended SDK. More licenses for this component can be purchased any time by VeriLook SDK and MegaMatcher SDK customers.\u003c\/span\u003e\u003c\/p\u003e\n","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":40901737644134,"sku":"100319","price":20.65,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo_573be27f-af08-440f-a7b2-a093fb39d6d0.jpg?v=1711046857"},{"product_id":"fast-face-matcher-result","title":"Fast Face Matcher License","description":"\u003cspan data-mce-fragment=\"1\"\u003eThe Fast Face Matcher has the same functionality, as the Face Matcher. It matches 200,000 faces per second and is designed for large-scale biometric systems, which run on high-end PCs or servers hardware with at least Intel Core i7-4771 (3.5 GHz) processor. Multiple cluster nodes running this component may be used to increase system performance.\u003c\/span\u003e\u003cbr data-mce-fragment=\"1\"\u003e\n\u003cp data-mce-fragment=\"1\"\u003eSee the reliability and performance testing results on the MegaMatcher Standard and MegaMatcher Extended SDK Technical Specs tab for the comparison of matching modes and multi-modal template matching.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eMulti-biometric fused template matching can be achieved by combining the Fast Face Matcher component with Fingerprint, Voice and\/or Iris Matchers (regular or fast versions of them can be used depending on project implementation).\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eYou may see volume discount prices for this product (if applicable) by clicking on the button near the top right-hand corner of the screen below the \"Add to Cart\" button.\u003c\/p\u003e\n\u003cspan data-mce-fragment=\"1\"\u003eOne Fast Face Matcher license is included with MegaMatcher Standard SDK. Two Fast Face Matcher licenses are included with MegaMatcher Extended SDK. More licenses for this component can be purchased at any time by MegaMatcher SDK customers.\u003c\/span\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":40901737676902,"sku":"100320-2","price":456.17,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo.jpg?v=1711046859"},{"product_id":"face-verification-sdk","title":"Face Verification SDK","description":"\u003cspan data-mce-fragment=\"1\"\u003eThe Face Verification SDK is designed for integration of facial authentication into enterprise and consumer applications for mobile devices and PCs. The simple API of the library component helps to implement solutions like payment, e-services and all other apps that need enhanced security through biometric face recognition, while keeping their overall size small for easy deployment to millions of users.\u003cbr data-mce-fragment=\"1\"\u003e\u003c\/span\u003e\u003cspan data-mce-fragment=\"1\"\u003e\u003c\/span\u003e\n\u003cp data-mce-fragment=\"1\"\u003eDifferent liveness detection functionalities are included to implement anti-spoofing mechanism with the possibility of configuring the balance between security and usability of the application.\u003c\/p\u003e\n\u003ch4\u003eFeatures and Capabilities\u003c\/h4\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003cul class=\"complex\"\u003e\n\u003cli\u003eCompact library for deployment on mobile devices.\u003c\/li\u003e\n\u003cli\u003eBased on VeriLook technology with millions of deployments worldwide.\u003c\/li\u003e\n\u003cli\u003eLive face detection prevents spoofing.\u003c\/li\u003e\n\u003cli\u003eAndroid, iOS, Microsoft Windows, Mac OS X and Linux supported.\u003c\/li\u003e\n\u003cli\u003eProgramming samples in multiple languages included.\u003c\/li\u003e\n\u003cli\u003eReasonable prices, flexible licensing and free customer support.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003eThe Face Verification SDK is intended for developing applications which perform end-user identity verification in mass scale systems like:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003esocial networks and media sharing services.\u003c\/li\u003e\n\u003cli\u003eonline banking and e-shops;\u003c\/li\u003e\n\u003cli\u003egovernment e-services;\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003eThe Face Verification SDK is based on the\u003cspan\u003e VeriLook\u003c\/span\u003e\u003cspan\u003e \u003c\/span\u003ealgorithm, which provides advanced face localization, enrollment and matching using robust digital image processing algorithms based on deep neural networks. The SDK offers these features for large-scale identity verification systems:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cb\u003eLive face detection.\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003eA conventional face identification system can be tricked by placing a photo in front of the camera. Face Verification SDK is able to prevent this kind of security breach by determining whether a face in a video stream is \"live\" or a photograph. The liveness detection can be performed in passive mode, when the engine evaluates certain facial features, and in active mode, when the engine evaluates user's response to perform actions like blinking or head movements.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eFace image quality determination.\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003eA quality threshold can be used during face enrollment to ensure that only the best quality face template will be stored into database.\u003c\/li\u003e\n\u003cli\u003eTolerance to face position. The Face Verification SDK allows head roll, pitch and yaw variation up to 15 degrees in each direction from the frontal position.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eMultiple samples of the same face.\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003eBiometric template record can contain multiple face samples belonging to the same person. These samples can be enrolled from different sources and at different times, thus allowing improvement in matching quality. For example a person might be enrolled with and without beard or mustache, etc.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eFeatures generalization mode.\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003eThis mode generates the collection of the generalized face features from several images of the same subject. Then, each face image is processed, features are extracted, and the collections of features are analyzed and combined into a single generalized features collection, which is written to the database. This way, the enrolled feature template is more reliable and the face recognition quality increases considerably.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch4\u003eThe Face Verification SDK package includes:\u003c\/h4\u003e\n\u003cul\u003e\n\u003cli\u003e1000\u003cspan\u003e PRT\u003c\/span\u003e\u003cspan\u003e \u003c\/span\u003elicenses;\u003c\/li\u003e\n\u003cli\u003e1000\u003cspan\u003e LIT\u003c\/span\u003e\u003cspan\u003e \u003c\/span\u003elicenses;\u003c\/li\u003e\n\u003cli\u003e3 dongles for license management.\u003c\/li\u003e\n\u003cli\u003eLarger quantities of transaction licenses can be also ordered\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003ch3\u003eGeneral Specifications\u003c\/h3\u003e\n\u003cp\u003eThe Face Verification SDK architecture requires to account the performed operations on integrator's or end-user's server:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eIntegrators should ensure that encrypted connection is used for communications with the server.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eNo face images or templates are sent to the server\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003eduring all operations, which require communication with the server. The biometric data is kept on the client-side, only transaction accounting information is sent to and received from the server.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003eThe following operations are available via the high-level API:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cb\u003eFace template creation\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003e– a face is captured from camera and the face template is extracted for further usage in the face verification operation.\n\u003cul\u003e\n\u003cli\u003eThe server returns proprietary encrypted data as a result of an enrolment transaction that has been completed successfully.\u003c\/li\u003e\n\u003cli\u003eFace liveness can be optionally checked during this operation. ICAO compliance check can be optionally used to strengthen the liveness check.\u003c\/li\u003e\n\u003cli\u003eA token image of the enrolled face in accordance with ISO 19794-5 criteria can be optionally generated.\u003c\/li\u003e\n\u003cli\u003eThe template may be saved to any storage (database, file etc) together with custom metainformation (like person's name etc.). Note that the storage functionality is not part of the Face Verification SDK, although the programming samples include an example of such implementation).\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eFace verification\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003e– a face is captured from the camera and is verified against the face template which was created during the face template creation operation.\n\u003cul\u003e\n\u003cli\u003eFace liveness can be optionally checked during this operation. ICAO compliance check can be optionally used to strengthen the liveness check.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eTemplate import\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003e– a face template, which was created with VeriLook algorithm, can be imported into the application, based on Face Verification SDK. Later this template can be used for\u003cspan\u003e \u003c\/span\u003e\u003cb\u003eface verification\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003eoperation in the same way, as the native templates from the face template creation operation.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eLiveness check\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003e– this operation perform only liveness check of the provided face and only returns the result of the check. See the recommendations for the liveness check below on this page.\n\u003cul\u003e\n\u003cli\u003eIf the liveness check succeed, a token image of the enrolled face in accordance with ISO 19794-5 criteria can be optionally generated.\u003c\/li\u003e\n\u003cli\u003eICAO compliance check can be optionally used to strengthen the liveness check.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2 class=\"title_front\"\u003eBasic Recommendations for Facial Image and Posture\u003c\/h2\u003e\n\u003cp\u003eThe face recognition accuracy heavily depends on the quality of a face image. Image quality during enrollment is important, as it influences the quality of the face template.\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e32 pixels is the recommended minimal distance between eyes for a face on a video stream to perform face template extraction reliably. 64 pixels or more recommended for better face recognition results. Note that this distance should be native, not achieved by resizing the video frames.\u003c\/li\u003e\n\u003cli\u003eSeveral face enrollments are recommended for better facial template quality which results in improvement of recognition quality and reliability.\u003c\/li\u003e\n\u003cli\u003eAdditional enrollments may be needed when facial hair style changes, especially when beard or mustache is grown or shaved off.\u003c\/li\u003e\n\u003cli\u003eThe face recognition engine is intended for usage with near-frontal face images and has certain tolerance to face posture:\n\u003cul\u003e\n\u003cli\u003ehead roll (tilt) – ±15 degrees;\u003c\/li\u003e\n\u003cli\u003ehead pitch (nod) – ±15 degrees from frontal position.\u003c\/li\u003e\n\u003cli\u003ehead yaw (bobble) – ±15 degrees from frontal position.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2 class=\"title_front\"\u003eLive Face Detection\u003c\/h2\u003e\n\u003cp\u003eA live video stream from a camera is required for face liveness check:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eWhen the liveness check is enabled, it is performed by the face engine before feature extraction. If the face in the stream fails to qualify as \"live\", the features are not extracted.\u003c\/li\u003e\n\u003cli\u003eOnly one face should be visible in these frames.\u003c\/li\u003e\n\u003cli\u003eOptionally, ICAO compliance check can be used to strengthen the liveness check.\u003c\/li\u003e\n\u003cli\u003eUsers can enable these liveness check modes:\n\u003cul\u003e\n\u003cli\u003e\n\u003cb\u003eActive\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003e– the engine requests the user to perform certain actions like blinking or moving one's head.\n\u003cul\u003e\n\u003cli\u003e5 frames per second or better frame rate required.\u003c\/li\u003e\n\u003cli\u003eThis mode can work with both colored and grayscale images.\u003c\/li\u003e\n\u003cli\u003eThis mode requires the user to perform all requested actions to pass the liveness check.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003ePassive\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003e– the engine analyzes certain facial features while the user stays still in front of the camera for a short period of time.\n\u003cul\u003e\n\u003cli\u003eColored images are required for this mode.\u003c\/li\u003e\n\u003cli\u003e10 frames per second or better frame rate required.\u003c\/li\u003e\n\u003cli\u003eBetter score is achieved when users do not move at all.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003ePassive then active\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003e- the engine first tries the passive liveness check, and if it fails, tries the active check. This mode requires colored images.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eSimple\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003e– the engine analyzes certain facial features while the user stays still in front of the camera for a short period of time.\n\u003cul\u003e\n\u003cli\u003eColored images are required for this mode.\u003c\/li\u003e\n\u003cli\u003e10 frames per second or better frame rate required.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eCustom\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003e– the engine requires user to turn head in four directions (up, down, left, right), in a random order.\n\u003cul\u003e\n\u003cli\u003e5 frames per second or better frame rate required.\u003c\/li\u003e\n\u003cli\u003eThis mode can work with both colored and grayscale images.\u003c\/li\u003e\n\u003cli\u003eThis mode requires the user to perform all requested actions to pass the liveness check.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e \u003c\/p\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":40901737709670,"sku":"100330","price":1174.06,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/sl-face-verif-min.jpg?v=1711046861"},{"product_id":"face-image-processing","title":"Face Image Processing","description":"\u003cp data-mce-fragment=\"1\"\u003eThe Face Image Processing component creates face templates from face images and is designed to be used in high-volume server applications, which run on server hardware with at least Intel Xeon Gold 6126 (2.6 GHz) processor. The component performs template extraction at a speed of 3,000 faces per minute.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cspan\u003eThe Face Image Processing component creates face templates from face images and is designed to be used in high-volume server applications, which run on server hardware with at least Intel Xeon Gold 6126 (2.6 GHz) processor. The component performs template extraction at a speed of 3,000 faces per minute.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eThe Face Image Processing component can generalize a face template from several images that include the same face to improve the template's quality.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eThe component also allows to integrate JPEG 2000 with Lossy and Lossless Face Profiles support into systems based on MegaMatcher SDK.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eDevice Manager software allows to perform simultaneous capture from multiple cameras. Integrators can write plug-ins to support their cameras or other devices using the plug-in framework provided with the Device Manager.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eThe Face Image Processing component also includes proprietary algorithms, which provide these advanced functionalities after facial template extraction:\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003ePerson's gender recognition.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eEmotions detection: confidence values returned for neutral mood, anger, disgust, fear, happiness, sadness and surprise.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eFacial feature points extraction for each person from an image.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eAge estimation for each person from an image.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eAdditional face attributes detection: smile, open-mouth, blink (closed-eyes), glasses, dark-glasses, beard and mustache.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eLive face detection can be used for determining whether a face in a video stream belongs to a real human or is a photo. See recommendations for live face detection for more information.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003eCaptured faces can be checked for compliancy with ICAO requirements. These requirements are checked:\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eimage pixelation, washed out colors;\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003ebackground uniformity;\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eface darkness, skin tone, skin reflections, glasses reflections;\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003ered eyes, looking away eyes (the red eyes can be corrected automatically).\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003eThe Face Image Processing component can provide token face images * compatible with the Face Image Format as in ISO\/IEC 19794 standard. This face image format enables range of applications on variety of devices, including devices that have limited resources required for data storage, and improves recognition accuracy by specifying data format, scene constraints (lighting, pose), photographic properties (positioning, camera focus) and digital image attributes (image resolution, image size). The following features are available:\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eFace Token Image creation from an image containing human face using eye coordinates which may be either hand marked or detected automatically using Neurotechnology face detection algorithm.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eFace is detected and eye coordinates are acquired using state-of-the-art Neurotechnology face detection and recognition algorithm.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eGeometrical face image normalization according to the proportions and photographic properties, which are specified in ISO\/IEC 19794 standard.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eIntelligent image padding algorithm for cutting off parts of token face image as specified in ISO\/IEC 19794 standard.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eEvaluation of the created token face image for the following quality criteria suggested in ISO\/IEC 19794 standard:\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eBackground uniformity – the background in the token face image should be uniform, not cluttered.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eSharpness – the token face image should not be blurred.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eToo light or too dark images – the token face image should not be too dark or too light.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eExposure range of an image – the token face image should have a reasonable exposure range to represent as much details of the subject in the image as possible.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eEvaluation of the token face image quality based on suggestions of ISO\/IEC 19794 standard (using the quality criteria above).\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003eThe Face Image Processing component allows to integrate support for facial image format standards with new or existing biometric systems based on MegaMatcher SDK. These biometric standards are supported:\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eBioAPI 2.0 (ISO\/IEC 19784-1:2006) (Framework and Biometric Service Provider for Face Identification Engine)\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eCBEFF V1.2 (ANSI INCITS 398-2008) (Common Biometric Exchange Formats Framework)\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eCBEFF V2.0 (ISO\/IEC 19785-1:2006 with Amd. 1:2010, 19785-3:2007 with Amd. 1:2010) (Common Biometric Exchange Formats Framework)\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eCBEFF V3.0 (ISO\/IEC 19785-3:2015) (Common Biometric Exchange Formats Framework)\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eISO\/IEC 19794-5:2005 (Biometric Data Interchange Formats - Face Image Data)\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eISO\/IEC 19794-5:2011 (Biometric Data Interchange Formats - Face Image Data)\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eANSI\/INCITS 385-2004 (Face Recognition Format for Data Interchange)\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eANSI\/NIST-CSL 1-1993 (Data Format for the Interchange of Fingerprint, Facial, \u0026amp; SMT Information)\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eANSI\/NIST-ITL 1a-1997 (Data Format for the Interchange of Fingerprint, Facial, \u0026amp; SMT Information)\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eANSI\/NIST-ITL 1-2000 (Data Format for the Interchange of Fingerprint, Facial, \u0026amp; SMT Information)\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eANSI\/NIST-ITL 1-2007 (Data Format for the Interchange of Fingerprint, Facial, \u0026amp; Other Biometric Information)\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eANSI\/NIST-ITL 1a-2009 (Data Format for the Interchange of Fingerprint, Facial, \u0026amp; Other Biometric Information)\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eANSI\/NIST-ITL 1-2011 (Data Format for the Interchange of Fingerprint, Facial, \u0026amp; Other Biometric Information)\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eANSI\/NIST-ITL 1-2011 Update:2013 Edition 2 (Data Format for the Interchange of Fingerprint, Facial, \u0026amp; Other Biometric Information)\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eANSI\/NIST-ITL 1-2011 Update:2015 (Data Format for the Interchange of Fingerprint, Facial, \u0026amp; Other Biometric Information)\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003eOne Face Image Processing component license is included with MegaMatcher 11.0 Standard SDK and MegaMatcher 11.0 Extended SDK. The license can be used on Microsoft Windows or Linux x86_64 platform. More licenses for this component can be purchased any time by MegaMatcher 11.0 SDK customers.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eNote: Token in this context is used as \"symbolic image, good enough image for machine recognition.\" Token Image as in ISO\/IEC19794-5: \"A Face Image Type that specifies frontal images with a specific geometric size and eye positioning based on the width and height of the image. This image type is suitable for minimizing the storage requirements for computer face recognition tasks such as verification while still offering vendor independence and human verification (versus human examination which requires more detail) capabilities.\"\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eWhen ordering 50 or more licenses, call for pricing.\u003c\/p\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":40901737742438,"sku":"100335","price":1689.52,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo_5b8f491a-1c97-4e02-9679-07bc40bae9e7.jpg?v=1711046863"},{"product_id":"fast-iris-matcher-license","title":"Fast Iris Matcher License","description":"\u003cp data-mce-fragment=\"1\"\u003eThe Fast Iris Matcher component is intended for large-scale biometric systems. The component includes a \u003cstrong\u003efast matching mode\u003c\/strong\u003e\u003cspan data-mce-fragment=\"1\"\u003e \u003c\/span\u003eand also has the same matching modes as the regular\u003cspan data-mce-fragment=\"1\"\u003e Iris Matcher\u003c\/span\u003e.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eMulti-biometric fused template matching can be achieved by combining the Fast Iris Matcher component with Fingerprint and\/or Face Matchers (regular or fast versions of them can be used depending on project implementation).\u003c\/p\u003e\n\u003cp\u003eSee the reliability and performance testing results on the MegaMatcher Standard and MegaMatcher Extended SDK Technical Specs tab for the comparison of matching modes and multi-modal template matching.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eOne Iris Matcher license is included with VeriEye (Current Version) Standard SDK, VeriEye (Current Version) Extended SDK, MegaMatcher (Current Version) Standard SDK and MegaMatcher (Current Version) Extended SDK. More licenses for this component can be purchased any time by VeriEye (Current Version) SDK and MegaMatcher (Current Version) SDK customers.\u003c\/p\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":40901737775206,"sku":"100425","price":675.81,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo200523-2-min_579bf6b5-8d3b-41c2-982d-c3b54db5f0c0.jpg?v=1711046865"},{"product_id":"fast-palm-print-matcher","title":"Fast Palm Print Matcher","description":"\u003cdiv data-mce-fragment=\"1\"\u003eThe Palm Print Fast Matcher component performs palm print template matching in 1-to-1 (verification) and 1-to-many (identification) modes. The component matches 4,000 palmprints per second and is designed for large-scale AFIS and biometric systems, which run on high-end PCs or servers hardware with at least Intel Core i7-4771 (3.5 GHz) processor.\u003cbr data-mce-fragment=\"1\"\u003e\n\u003c\/div\u003e\n\u003cdiv data-mce-fragment=\"1\"\u003ePalm print template matching requires much more time than fingerprints, as palm images are much larger compared to fingerprint images, but have similar features density. Full palm print templates may contain about 2,000 minutiae compared to about 50 for fingerprint templates.\u003cbr data-mce-fragment=\"1\"\u003e\n\u003c\/div\u003e\n\u003cdiv data-mce-fragment=\"1\"\u003eMegaMatcher palm print template matching algorithm may be configured to use more than one processor core on multi-core processors allowing to increase template matching speed.\u003cbr data-mce-fragment=\"1\"\u003e\n\u003c\/div\u003e\n\u003cdiv data-mce-fragment=\"1\"\u003eOne license for the Fast Palm Print Matcher component is included in MegaMatcher 11.1 Standard SDK and MegaMatcher 11.1 Extended SDK. More licenses for this component can be purchased any time by MegaMatcher 11.1 SDK customers.\u003c\/div\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":40901737807974,"sku":"100535","price":675.81,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo_4abb4b3a-e063-4b4a-8e75-4bea4a46dfec.jpg?v=1711046867"},{"product_id":"digital-onboarding","title":"Digital Onboarding","description":"","brand":"Fulcrum Biometrics, Inc","offers":[{"title":"Default Title","offer_id":40901737906278,"sku":null,"price":0.0,"currency_code":"GBP","in_stock":true}]},{"product_id":"criminal-live-scan","title":"Criminal Live Scan","description":"","brand":"Fulcrum Biometrics, Inc","offers":[{"title":"Default Title","offer_id":40901737939046,"sku":null,"price":0.0,"currency_code":"GBP","in_stock":true}]},{"product_id":"cmitech-ef-45nc-dual-iris-recognition-system","title":"CMITech EF-45NC Dual Iris Recognition System","description":"\u003cp\u003eThe EF-45Nc next generation iris recognition system provides unprecedented subject ease of use through a highly innovative and intuitive user positioning approach. Subjects will view their own face in a front-facing, high resolution 5.0 inch color display to position themselves correctly within the real-time graphic interface. They will intuitively and naturally move to the correct position by sim- ply centering and sizing their face image to the box within the display. In addition, the position- ing box and the top border turn green to indicate proper distance positioning, after which the iris biometrics images are automatically collected, provided that the real time image quality metrics are satisfied. Vocalized commands give additional positioning guidance in real time.\u003c\/p\u003e\n\u003cp\u003eNew for the EF-45Nc, a time-of-flight (TOF) proxim-ity and distance sensor is integrated for fast and precise detection of all subjects. The system now features a faster tilt motor, and proprietary “deep learning” based face detector algorithm. Together, the system is faster, smooth- er and even more intuitive than ever before. The deep-learning face detector also enhances opera- tion in bright ambient light for deployment posi- tioning flexibility. Now, capturing highest quality iris biometrics images is fast, simple and fully intuitive for all subjects, including non-acclimated ones.\u003c\/p\u003e\n\u003cp\u003eThe EF-45Nc operates at an expansive capture range of 35 to 45 cm in enrollment mode. In rec- ognition mode, the capture range is extended to 32 to 45 cm, further increasing positioning flexibil- ity and ease of use.\u003c\/p\u003e\n\u003cp\u003eThe system captures high quality face images simultaneously with iris image capture. On board face recognition is optional.\u003c\/p\u003e\n\u003cp\u003eThe EF-45Nc is an embedded system that includes its own Quard mainboard to manage all face and iris imaging processes.\u003c\/p\u003e\n\u003cp\u003eThe normal external communication to host systems and clients is through TCP\/IP via an Ethernet connection, but USB connectivity to a local PC host is available. The embedded architecture allows for on-board iris and face template generation and matching against a local data base. The EF-45Nc is offered in two basic hardware configurations: the AC version is for physical access control (PACS), time \u0026amp; attendance and similar applications, and includes an embedded MiFare card reader, a wall mount bracket and a full set of I\/O connectors; the ID version is for general identity management applications and does not include the card reader or the full connector set.\u003c\/p\u003e\n\u003cp\u003eThe EF-45Nc is fully backward compatible with the prior generation EF-45 system, which means that no API changes are required for systems integrators.\u003c\/p\u003e\n\u003ch5\u003eInnovative, Intuitive Subject Positioning\u003c\/h5\u003e\n\u003cp\u003eThe EF-45Nc’s TOF sensor detects subjects from over 1.0 meter from the system; the subject’s face is immediately displayed on the 5.0 inch high resolution color display. For proper positioning, the subject will naturally center his face by simply making his or her face fit the positioning “guide box”. Vocalized instructions also command the user to move forward or back to get into range. When in the proper range, the guide box and top border turn green, indicating to the subject to stop and wait until the image capture process is completed. Like a smart phone “selfie” image, this interface is highly intuitive, with typical capture times of 0.5 seconds from proper positioning.\u003c\/p\u003e\n\u003ch5\u003eColor visual cues for proper distance positioning\u003c\/h5\u003e\n\u003cbr\u003e\n\u003ch5\u003eKey Features\u003c\/h5\u003e\n\u003ctable style=\"width: 70%;\" class=\"data\" cellspacing=\"2\" cellpadding=\"2\" border=\"1\" bgcolor=\"#FFFFFF\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e\u003cb\u003eFeature\u003c\/b\u003e \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e\u003cb\u003eUser Advantages\u003c\/b\u003e \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eState-of-the-art optical design\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eThe optical design includes utilizing highest quality optics and very fast shutter speeds, which allows the systems to exceed industry standards for image quality. \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eAdvanced, proprietary stereoscopic eye localization \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eThe EF-45Nc accurately locates the position of both eyes in 3D to optimize subject ease of positioning and iris image quality. This function enables the fast and reliable subject distance positioning indicators shown as blue, green or red color distance positioning codes. \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eHighest image quality \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eMeets or exceeds the ISO 19794-6 2011 and ISO 29794-6 iris imaging specifications. \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eCompact, lightweight design\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eOptimizes placement or mounting options, including wall, swing arm, or eGate mounting solutions. \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eSimplest of user instructions \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eVery simple and repeatable subject instructions:\u003cbr\u003e• Position face within guide box in display (like smartphone “selfie”)\u003cbr\u003e • Move toward the system to size head to box\u003cbr\u003e • Once within range, the box and indicator bar will turn green to indicate proper positioning \u003cbr\u003e\u003cbr\u003eCapture is automatic once subject is in proper position and real time image quality metrics parameters are met.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eStand-off distance and depth of capture in enrollment mode \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e35 to 45 cm, ensuring robust, fast and easy positioning. Comfortable range for subjects in wide variety of desktop, countertop, kiosk or wall mount placements. \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eExtended depth of capture in recognition mode\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eDepth of capture can be extended to a range of 32 to 45 cm in recognition mode (not necessarily ISO compatible). Intended for small to medium scale access control deployments. Selectable in SDK.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eReal time image quality metrics \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eImage quality metrics included in capture algorithm:\u003cbr\u003e• Subject gaze angle (i.e. whether the subject is looking directly ahead at the imager)\u003cbr\u003e• Subject motion\u003cbr\u003e• Focus\u003cbr\u003e• Usable iris area (occlusion) \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eFace image capture \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eA face image is always collected at same time as capture of iris images, so that the data record consists of one face image and two iris images.\u003cbr\u003e\u003cbr\u003eNote: the face images do not qualify as ISO standard, and therefore are not intended for large scale face recognition purposes. They are intended for small scale face recognition and manual verification of the subject’s identity. Face images also remain in the log file to visually verify who was authenticated.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eFace recognition \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eOptional. Contact CMITech for algorithm selection and pricing.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eVery wide interpupillary distance range \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eThe wide interpupillary distance range accommodates all adults and young children, making it ideal for large scale, public authentication programs.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eLarge on-board data bases for on- board identification and authen- tication \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eStandard on-board (local) iris data base of 100,000 subjects (iris template-pairs), with matching speed of about 0.5 second in 1:N mode.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eTemplate-on-card \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eSupported for MiFare and DesFire cards\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eCable connectors\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eFor AC version, plug-in connector kit for all cabling (except RJ-45 Ethernet) included in accessories package.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eWiFi\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eOptional, field installable WiFi dongle for ease of networking installation. (Contact CMITech for WiFi dongle specification for each country).\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eCard reader\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eStandard in AC version only: embedded MiFare card reader for support of dual factor authentication, or backup authentication for special case users.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eLanguage support\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eDisplay languages of English, Korea, Traditional Chinese, Simpli- fied Chinese, Japanese, Spanish, Italian, Arabic, and Russian.\u003cbr\u003e\u003cbr\u003eVocalizations for positioning can be modified by local systems integrators through modification of on-board .wav files.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003ctable style=\"width: 70%;\" class=\"data\" cellspacing=\"2\" cellpadding=\"2\" border=\"1\" bgcolor=\"#FFFFFF\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eEmbedded CPU \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eQuad Cortex-A55, 2GHz \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eOn-board Iris algorithm for encoding and matching\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eStandard in all configurations \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eFlexible Software Development Kit (SDK) configurations \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eHigh Level SDK’s offered in C# (.NET) and C++ versions. Includes host side reference application to connect to EF-45 resident services layer so that integrator does not need to program EF-45 device. \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eConfiguration Utility software application \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eThis host side software application provides centralized (network) control and setup of system configuration, Wiegand settings, and IP address settings, as well as providing for centralized FW upgrades.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eCompatibility with prior generation EF-45\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eFully backward compatible to prior SDK versions for the EF-45, which means that no API changes are necessary when installing in legacy solutions. \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eDimensions\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e166 x 166 x 43 mm (6.5 x 6.5 x 1.7 inches) without mounting wall plate\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eWeight \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e630 g without wall plate \u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eOn-board data storage\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eStandard: 100,000 iris template pairs with match speed in 1:N mode of about 0.5 second.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eDual factor authentication \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eIris with either smart card and PIN as second factor\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eIris image pixel resolution \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eMeets ISO 19794-6 2011 and ISO 29794-6 iris imaging standards\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eIris image output \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e640 x 480 pixels, 8 bit depth, supports multiple formats\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eAdjustable FAR (false accept rate) \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eAdjustable iris algorithm threshold range of 10\u003csup\u003e-5\u003c\/sup\u003e to 10\u003csup\u003e-14\u003c\/sup\u003e FMR at 10\u003csup\u003e-6\u003c\/sup\u003e FNMR. Default is 10\u003csup\u003e-8\u003c\/sup\u003e.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eEnrollment mode operational iris imaging distance (stand-off range) and depth of field \u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e35 to 45 cm range (7 cm depth of capture range) in enrollment mode. Meets ISO 19794-6 2011 and 29794-6 specifications.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eRecognition mode operational iris imaging distance\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eRecognition mode provides up to 32 to 45 cm range (13 cm depth of capture) for small scale applications. Does not necessarily meet ISO specifications. Range selectable in SDK.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eIris positioning indicators\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eFace positioning within box in LCD serves to center users face in X-Y dimensions.\u003cbr\u003e\u003cbr\u003eSubject will fit size of face to box size within LCD display for distance (Z) positioning, with simultaneous color bar display for correct distance positioning:\u003cbr\u003eBlue: too far away\u003cbr\u003eGreen: OK\u003cbr\u003eRed: too close\u003cbr\u003e\u003cbr\u003eSupplemental voice distance feedback also simultaneous. Vocalizations convertible to local language via .wav file substitution.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eAuto tilt\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eInternal auto tilt range of +25 to -20 degrees, which corresponds to height range of approximately 40 cm. System can be mounted at any height to accommodate local user population.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eTime of iris image capture\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eTypically about 0.5 second from time the subject’s eyes are properly placed within capture volume.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eIR illumination for iris imaging\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eTypically 0.5 second from time the subject’s eyes are properly placed within capture volume.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eIR illumination for iris imaging\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eDual wavelength LEDs (spectral range of 700 to 900 nm) that con- forms to ISO best practices for iris imaging.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eFace image capture\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eStandard 24 bit color and NIR images, both accessible from SDK\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eFace recognition\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eOptional on-board encoding and matching\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eAudio\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e24 bit, 1 W embedded speaker\u003cbr\u003eLine-out connector for external speaker\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eOperating temperature range\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e0 to 45 ̊C\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eHumidity range\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e10 to 90% RH, non-condensing\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eIlluminator eye safety standard\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eIEC 62471\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eNetwork interface, standard\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e10\/100 Base-T Ethernet (RJ45 connector)\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eRFID Card reader\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eIntegrated CMITech MiFare \/ DesFire reader (in EF-45 AC version only)\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eMounting\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003e¼ - 20 UNC (consumer camera tripod mount type) standard\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eKensington lock slot\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eStandard\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003ePhysical access control (EF-45AC) version accessories\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eDetachable wall mount plate for easy wall installation. Terminal and wired connectors for: Wiegand in\/out, RS-232, RS-485, 2X TTL (GPIO) inputs, 1 dry contact relay\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eID management (EF-45ID) version accessories\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eTerminal and wired connectors for: RS-232, RS-485, 2X TTL (GPI), 1 dry contact relay\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\"\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003ePower supply requirement\u003c\/span\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cspan style=\"font-size: 11pt; font-family: Calibri, sans-serif;\"\u003eInput 12V to 24V DC, 3.0A.\u003cbr\u003e AC power adapter included in all versions.\u003c\/span\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e","brand":"CMITech Company, Ltd.","offers":[{"title":"Default Title","offer_id":40901738135654,"sku":"102166","price":997.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/cmitech.jpg?v=1711046872"},{"product_id":"enhanced-customer-experience-solution","title":"Enhanced Customer Experience Solution","description":"","brand":"Fulcrum Biometrics, Inc","offers":[{"title":"Default Title","offer_id":40901738168422,"sku":null,"price":0.0,"currency_code":"GBP","in_stock":true}]},{"product_id":"face-extractor-license","title":"Face Extractor License","description":"\n\u003cp\u003e\n\tFace Extractor creates face templates from face images.\n\t\t\t\t\t\t\t\t\tThe Extractor can generalize a face template from several \nimages that include the same face to improve the template's quality.\n\u003c\/p\u003e\n\u003cp\u003e\n\t\t\t\t\t\t\t\t\tDevice Manager software allows to perform \n\t\u003cstrong\u003esimultaneous capture from multiple cameras\u003c\/strong\u003e.\n\t\t\t\t\t\t\t\t\tIntegrators can write \n\t\u003cstrong\u003eplug-ins to support their cameras\u003c\/strong\u003e or other devices using the plug-in framework provided with the Device Manager.\n\u003c\/p\u003e\n\u003cp\u003e\n\t\t\t\t\t\t\t\t\tThe component extracts a single face template in \n\t\u003cstrong\u003e1.34 seconds\u003c\/strong\u003e.\n\t\t\t\t\t\t\t\t\tThe specified performance requires a \n\t\u003cstrong\u003ePC or laptop\u003c\/strong\u003e with at least Intel \u003cstrong\u003eCore 2 Q9400\u003c\/strong\u003e (2.67 GHz) processor.\n\u003c\/p\u003e\n\u003cp\u003e\n\t\t\t\t\t\t\t\t\tOne Face Extractor license is included with VeriLook 5.5 \nStandard SDK, VeriLook 5.5 Extended SDK, MegaMatcher 5.0 Standard SDK \nand MegaMatcher 5.0 Extended SDK.\n\t\t\t\t\t\t\t\t\tMore licenses for this component can be purchased any time by \nVeriLook 5.5 SDK and MegaMatcher 5.0 SDK customers.\n\u003c\/p\u003e\n\n","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":40901738201190,"sku":"100309","price":16.53,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/80neurotlogo6.jpg?v=1711046875"},{"product_id":"copy-of-fingerprint-extractor-license","title":"Fingerprint Extractor License","description":"Fingerprint Extractor creates fingerprint templates from fingerprint images. Image quality control can be applied to accept only good quality fingerprint images.\u003cbr data-mce-fragment=\"1\"\u003eThe Fingerprint Extractor can generalize a fingerprint template from several images that contain the same fingerprint to improve the template's quality.\u003cbr data-mce-fragment=\"1\"\u003eThe component extracts a single fingerprint template in 1.34 seconds. The specified performance requires a PC or laptop with at least Intel Core 2 Q9400 (2.67 GHz) processor.\u003cbr data-mce-fragment=\"1\"\u003eOne Fingerprint Extractor license is included with VeriFinger (Current Version) Standard SDK, VeriFinger (Current Version) Extended SDK, MegaMatcher (Current Version) Standard SDK and MegaMatcher (Current Version) Extended SDK. More licenses for this component can be purchased any time by VeriFinger (Current Version) SDK and MegaMatcher (Current Version) SDK customers.\n","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":40901738233958,"sku":"100217","price":20.4,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/fingerprint_EXTRACTOR_ae02272f-507e-4caa-be9f-ee76a8092bf7.jpg?v=1711046877"},{"product_id":"iritech-irishield-usb-bk2121u-iris-camera","title":"IriTech IriShield-USB BK2121U Iris Camera","description":"\u003cp\u003e\n\tIriShield™ Series is an ultra-compact, auto-capture camera module, complete with onboard iris recognition and a PKI-based security infrastructure that ensures complete data security.\n\t\u003cbr\u003e\n\tWith its low cost, IriShield™ Series will lower the entry barrier to deploying iris biometric solutions in all sorts of applications.\n\u003c\/p\u003e\n\u003ch2\u003eProduct Offering\u003c\/h2\u003e\n\u003cp style=\"color: rgb(51, 51, 51); font-weight: normal;\"\u003e\n\tThe IriShield series eye cameras are offered in three packages (Encased Device, Module, and Chip \u0026amp; Camera Set) with diverse options to developers and manufacturers for integration with various applications. Please be sure to select the correct package for your requirements. This item is an encased device.\n\u003c\/p\u003e\n\u003ch2\u003eKey Features\u003c\/h2\u003e\n\u003cul style=\"margin-left: 40px;\"\u003e\n\t\u003cli\u003e\u003cb\u003eAuto-Capture, Template Generation \u0026amp; Matching\u003c\/b\u003e\u003c\/li\u003e\n\t\u003cli\u003e\n\u003cstrong\u003eSecure on-board processing\u003c\/strong\u003e\n\t\u003cul\u003e\n\t\t\u003cli\u003eAll key functions like iris capture, iris recognition, key generation, encryption, and digital signature are done on-board in a secure environment.\u003c\/li\u003e\n\t\u003c\/ul\u003e\n\t\u003c\/li\u003e\n\t\u003cli\u003e\u003cstrong\u003eTamper-proof\u003c\/strong\u003e\u003c\/li\u003e\n\t\u003cli\u003e\n\u003cstrong\u003eSecure data \u0026amp; communication\u003c\/strong\u003e\n\t\u003cul\u003e\n\t\t\u003cli\u003eEach IriShield device has its own 2048 bit RSA key securely generated on-board for encryption and digital signature.\u003c\/li\u003e\n\t\t\u003cli\u003eKey device in IriTech’s secure end-to-end biometric solution.\u003c\/li\u003e\n\t\t\u003cli\u003eOTP\/Password\/Timestamp can be seamlessly integrated with IriShield.\u003c\/li\u003e\n\t\u003c\/ul\u003e\n\t\u003c\/li\u003e\n\t\u003cli\u003e\u003cstrong\u003eUltra-compact, light weight\u003c\/strong\u003e\u003c\/li\u003e\n\t\u003cli\u003e\u003cstrong\u003eLow power consumption\u003c\/strong\u003e\u003c\/li\u003e\n\t\u003cli\u003e\n\u003cstrong\u003eCost effective\u003c\/strong\u003e\n\t\u003cul\u003e\n\t\t\u003cli\u003eMost economical for projects of any size.\u003c\/li\u003e\n\t\u003c\/ul\u003e\n\t\u003c\/li\u003e\n\t\u003cli\u003e\n\u003cstrong\u003eVarious OS supported\u003c\/strong\u003e\n\t\u003cul\u003e\n\t\t\u003cli\u003eWindows 32\/64bit, Linux 32bit, WinCE, Embedded Linux, and Android\u003c\/li\u003e\n\t\u003c\/ul\u003e\n\t\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003ctable style=\"width: 100%;\" width=\"100%\" cellspacing=\"0\" cellpadding=\"3\" border=\"1\" bgcolor=\"#FFFFFF\"\u003e\n\u003ctbody\u003e\n\u003ctr height=\"50\"\u003e\n\t\u003ctd style=\"width: 639px; height: 48px;\" colspan=\"3\" height=\"50\" bgcolor=\"f4f4f4\"\u003e\n\t\t\n\t\t\tProduct name : \u003cstrong\u003eIriShield-USB MK 2120U \/ MO2120 \/ MO 2121\/ BK 2121U \/ BO 2121\u003c\/strong\u003e\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"50\"\u003e\n\t\u003ctd style=\"width: 639px; height: 48px;\" colspan=\"3\" height=\"50\" bgcolor=\"f4f4f4\"\u003e\n\t\t\n\t\t\tIriShield-USB Serial supports USB Interface, Security Infrastructure,\n and various OS such as Windows family, Linux family, WinCE, Embedded \nLinux, and Android.\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"34\"\u003e\n\t\u003ctd style=\"width: 123px; height: 33px;\" height=\"34\" bgcolor=\"f4f4f4\"\u003e\n\t\t\n\t\t\tCapture Mode\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 515px;\" rowspan=\"1\" colspan=\"2\"\u003e\n\t\t\n\t\t\tAuto capture\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"34\"\u003e\n\t\u003ctd style=\"width: 123px; height: 33px;\" rowspan=\"4\" colspan=\"1\" height=\"34\" bgcolor=\"f4f4f4\"\u003e\n\t\t\n\t\t\tCapture Distance\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 78px;\"\u003e\n\t\t\n\t\t\tMK 2120U\n\t\t\n\t\t\u003cbr\u003e\n\t\t\tMO 2120\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 435px;\"\u003e\n\t\t\n\t\t\t4.7 cm - 5.3 cm (1.8 inches -2.1 inches) from the image sensor\n\t\t\n\t\t\t\t\t\t\t(Optimal distance = 5 cm (2 inches), Focal depth = 6 mm (0.2 inch)\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"width: 78px;\"\u003e\n\t\t\t\tMO 2121\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 435px;\"\u003e\n\t\t\n\t\t\t13.0 cm - 14.0 cm (5.1 inches -5.5 inches) from the image sensor\n\t\u003cbr\u003e\n\t\t\t(Optimal distance = 13.5 cm (5.3 inches), Focal depth = 1.0 cm (0.4 inch),\u003cbr\u003e\n\t\t\n\t\t\t\t\t\t\tField of View = 3.3 cm x 2.4 cm at 13.5 cm (1.3 inches x 0.9 inch at 5.3 inches)\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"width: 78px;\"\u003e\n\t\t\t\tBK 2121U\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 435px;\"\u003e\n\t\n\t\t\t13.5 cm - 14.5 cm (5.3 inches -5.7 inches) from the front of camera Lens\n\t\t\u003cbr\u003e\n\t\t\t(Optimal distance = 14 cm (5.5 inches), Focal depth = 1.0 cm (0.4 inch),\n\t\t\u003cbr\u003e\n\t\t\t\t\t\t\tField of View = 3.3 cm x 2.4 cm at 15 cm (1.3 inches x 0.9 inch at 5.9  inches)\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"width: 78px;\"\u003e\n\t\t\t\tBO 2121\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 435px;\"\u003e\n\t\t\n\t\t\t14 cm - 15 cm (5.5 inches -5.9 inches) from the front of camera Lens\n\t\t\u003cbr\u003e\n\t\t\t(Optimal distance = 14.5 cm (5.7 inches), Focal depth = 1.0 cm (0.4 inch),\n\t\t\u003cbr\u003e\n\t\t\t\t\t\t\tField of View = 3.3 cm x 2.4 cm at 15 cm (1.3 inches x 0.9 inch at 5.9  inches)\n\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"34\"\u003e\n\t\u003ctd style=\"width: 123px; height: 33px;\" height=\"34\" bgcolor=\"f4f4f4\"\u003e\n\t\t\n\t\t\tImage Format\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 515px;\" rowspan=\"1\" colspan=\"2\"\u003e\n\t\t\n\t\t\tISO Standard 19794-6 (2005 \u0026amp; 2011), (640 x 480 Pixels, 8 bit Grayscale), full support of K1, K2, K3, K7\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"34\"\u003e\n\t\u003ctd style=\"width: 123px; height: 33px;\" height=\"34\" bgcolor=\"f4f4f4\"\u003e\n\t\n\t\t\tSensor Resolution\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 515px;\" rowspan=\"1\" colspan=\"2\"\u003e\n\t\n\t\t\tVGA\n\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"34\"\u003e\n\t\u003ctd style=\"width: 123px; height: 33px;\" rowspan=\"5\" colspan=\"1\" height=\"34\" bgcolor=\"f4f4f4\"\u003e\n\t\t\n\t\t\tDimensions\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 78px;\"\u003e\n\t\n\t\t\tMK 2120U\n\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 435px;\"\u003e\n\t\t\t\t51.2mm x 92.6mm x 15.1mm (2 inches x 3.6 inches x 0.59 inch)\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"width: 78px;\"\u003e\n\t\t\t\tMO 2120\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 435px;\"\u003e\n\t\t\n\t\t\tIriShield-USB Board: 36mm x 40mm x 6.9mm (1.4 inches x 1.6 inches  x  0.3 inch)\n\t\t\u003cbr\u003e\n\t\t\t\t\t\t\tCamera Module: 30mm x 15.4mm x 7.1mm (1.2 inches x 0.6 inch x 0.3 inch)\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"width: 78px;\"\u003e\n\t\t\t\tMO 2121\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 435px;\"\u003e\n\t\t\n\t\t\tIriShield-USB board: 36mm x 40mm x 6.9mm (1.4 inches x 1.6 inches x 0.3 inch)\n\t\t\u003cbr\u003e\n\t\t\t\t\t\t\tCamera module: 48mm x 17.5mm x 7.9mm (1.9 inches x 0.7 inch x 0.3 inch)\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"width: 78px;\"\u003e\n\t\t\t\tBK 2121U\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 435px;\"\u003e\n\t\t\n\t\t\tIriShield-USB: 124 mm x 63.2mm x 42.5 mm (4.9 inches x 2.49 inches x 1.68 inches)\n\t\t\u003cbr\u003e\n\t\t\t\t\t\t\tGoggle: 200 mm x 145 mm x 72 mm (7.9 inches x 5.7 inches x 2.8 inches)\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"width: 78px;\"\u003e\n\t\t\t\tBO 2121\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 435px;\"\u003e\n\t\t\n\t\t\tIriShield-USB board: 47 mm x 40 mm x 6.9 mm (1.8 inches x 1.6 inches x 0.3 inch)\n\t\t\u003cbr\u003e\n\t\t\t\t\t\t\tCamera Module: 31 mm x 27 mm x 23.3 mm (1.2 inches x 1.1 inches x 0.9 inch)\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"34\"\u003e\n\t\u003ctd style=\"width: 123px; height: 33px;\" rowspan=\"3\" colspan=\"1\" height=\"34\" bgcolor=\"f4f4f4\"\u003e\n\t\t\n\t\t\tPower\n\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 78px;\"\u003e\n\t\t\n\t\t\tMK 2120U\n\t\t\u003cbr\u003e\n\t\t\tMO 2120\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 435px;\"\u003e\n\t\t\t\tSingle USB Bus Powered (DC +5V±5%) (Max power consumption=250mA)\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"width: 78px;\"\u003e\n\t\t\t\tMO 2121\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 435px;\"\u003e\n\t\t\t\tSingle USB Bus Powered (DC +5V±5%) (Max power consumption=290mA)\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"width: 78px;\"\u003e\n\t\t\n\t\t\tBK 2121U\n\t\t\u003cbr\u003e\n\t\t\t\t\t\t\tBO 2121\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 435px;\"\u003e\n\t\t\t\tSingle USB Bus Powered (DC +5V±5%) (Max power consumption=430mA)\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"34\"\u003e\n\t\u003ctd style=\"width: 123px; height: 33px;\" height=\"34\" bgcolor=\"f4f4f4\"\u003e\n\t\t\n\t\t\tIllumination\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 515px;\" rowspan=\"1\" colspan=\"2\"\u003e\n\t\t\n\t\t\tInfrared LED\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"34\"\u003e\n\t\u003ctd style=\"width: 123px; height: 33px;\" rowspan=\"3\" colspan=\"1\" height=\"34\" bgcolor=\"f4f4f4\"\u003e\n\t\t\n\t\t\tEnvironmental\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 78px;\"\u003e\n\t\t\n\t\t\tMK 2120U\n\t\t\u003cbr\u003e\n\t\t\tMO 2120\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 435px;\"\u003e\n\t\t\t\t0 °C to + 45 °C (Operating);  10% to 90% Humidity (Non-Condensing)\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"width: 78px;\"\u003e\n\t\t\t\tMO 2121\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 435px;\"\u003e\n\t\t\t\t-20°C to +60°C (Storage); 0°C to +45°C (Operating)\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"width: 78px;\"\u003e\n\t\t\n\t\t\tBK 2121U\n\t\t\u003cbr\u003e\n\t\t\t\t\t\t\tBO 2121\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 435px;\"\u003e\n\t\t\t\t-20°C to +60°C (Storage); 0°C to +50°C (Operating)\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"34\"\u003e\n\t\u003ctd style=\"width: 123px; height: 33px;\" height=\"34\" bgcolor=\"f4f4f4\"\u003e\n\t\t\n\t\t\tUsage\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 515px;\" rowspan=\"1\" colspan=\"2\"\u003e\n\t\t\n\t\t\tIndoor;  Outdoor (avoid direct sunlight and bright reflections)\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"34\"\u003e\n\t\u003ctd style=\"width: 123px; height: 33px;\" height=\"34\" bgcolor=\"f4f4f4\"\u003e\n\t\t\n\t\t\tCompliance \u0026amp; Certificates\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 515px;\" rowspan=\"1\" colspan=\"2\"\u003e\n\t\t\n\t\t\tEye safety standard (IEC 62471:2006-07), RoHS\n\t\u003cbr\u003e\n\t\t\t\t\t\t\tFCC-Class A* ,  IP54*\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"34\"\u003e\n\t\u003ctd style=\"width: 123px; height: 33px;\" height=\"34\" bgcolor=\"f4f4f4\"\u003e\n\t\t\n\t\t\tResolution\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 515px;\" rowspan=\"1\" colspan=\"2\"\u003e\n\t\t\n\t\t\tSpatial : ≥ 60% @ 4.0 Lp\/mm, Pixel :  ≥  16 Pixels\/mm\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"34\"\u003e\n\t\u003ctd style=\"width: 123px; height: 33px;\" height=\"34\" bgcolor=\"f4f4f4\"\u003e\n\t\t\n\t\t\tConnectivity\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 515px;\" rowspan=\"1\" colspan=\"2\"\u003e\n\t\t\n\t\t\tUSB 2.0\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"34\"\u003e\n\t\u003ctd style=\"width: 123px; height: 33px;\" height=\"34\" bgcolor=\"f4f4f4\"\u003e\n\t\n\t\t\tProduct package\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 515px;\" rowspan=\"1\" colspan=\"2\"\u003e\n\t\t\n\t\t\tChip \u0026amp; Camera set, Module, Encased\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"34\"\u003e\n\t\u003ctd style=\"width: 123px; height: 33px;\" height=\"34\" bgcolor=\"f4f4f4\"\u003e\n\t\t\n\t\t\tSecurity\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 515px;\" rowspan=\"1\" colspan=\"2\"\u003e\n\t\t\n\t\t\tPKI (2048-bit) and AES (256-bit); X509 Certificate, PFX\/PKCS#12 Certificate , RSA key pair generated on-board\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"34\"\u003e\n\t\u003ctd style=\"width: 123px; height: 33px;\" height=\"34\" bgcolor=\"f4f4f4\"\u003e\n\t\t\n\t\t\tAncillary SW\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 515px;\" rowspan=\"1\" colspan=\"2\"\u003e\n\t\n\t\t\tDemo Application, Drivers, SDK (C\/C++, .NET C#\/VB, Java) with Sample codes\n\t\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr height=\"34\"\u003e\n\t\u003ctd style=\"width: 123px; height: 33px;\" height=\"34\" bgcolor=\"f4f4f4\"\u003e\n\t\t\n\t\t\tHost OS\n\t\t\n\t\u003c\/td\u003e\n\t\u003ctd style=\"width: 515px;\" rowspan=\"1\" colspan=\"2\"\u003e\n\t\t\n\t\t\tWindows Family, Linux Family, WinCE, Embedded Linux, and Android\n\t\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp\u003e\n\t* Encased model only\n\u003c\/p\u003e\n\u003cp\u003e\n\t※ Please specify Ancillary SW and Host OS before ordering\n\u003c\/p\u003e","brand":"Iritech, Inc.","offers":[{"title":"Default Title","offer_id":41331017973862,"sku":"102152","price":393.96,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/BK2121U.jpg?v=1714422347"},{"product_id":"lumidigm-v-series-v311-multispectral-fingerprint-scanner","title":"Lumidigm V-Series V311 Multispectral Fingerprint Scanner","description":"\n\u003cp\u003eThe Lumidigm Venus Series Biometric Fingerprint Sensors capture accurate and high-quality images by exposing the fingerprint surface and subsurface at the same time. You can depend on the V-Series sensors to return superior images on anyone, anytime, in any environment. Lumidigm's multispectral imaging technology simultaneously reads the surface and subsurface to capture clear, clean images every time-even when surface features are absent or hard to distinguish due to age, dirt, finger pressure, and skin or environmental conditions. Our sensors enroll and verify every fingerprint including those that thwart conventional sensors. Solve failure to enroll (FTE) and failure to acquire (FTA) issues with Lumidigm's V-Series. Eliminate performance problems associated with conventional fingerprint sensors. V-Series sensors protect against fake and spoof fingerprints by capturing detailed surface and deep tissue data. Using the biometric industry's best spoof detection technology, we provide the most secure and accurate sensors available.\u003c\/p\u003e\n\n\n\u003ch2\u003eLumidigm V-Series V311 Features\u003c\/h2\u003e\n\u003ch3\u003eSuperb Image Quality\u003c\/h3\u003e\n\u003cp\u003eLumidigm's multispectral imaging technology simultaneously reads the surface and subsurface to capture clear, clean images every time even when surface features are absent or hard to distinguish due to age, dirt, finger pressure, and skin or environmental conditions. Our sensors enroll and verify every fingerprint including those that thwart conventional sensors. Solve failure to enroll (FTE) and failure to acquire (FTA) issues with Lumidigm's V-Series.\u003c\/p\u003e\n\n\u003ch3\u003eSpoof detection\u003c\/h3\u003e\n\u003cp\u003eEliminate performance problems associated with conventional fingerprint sensors. V-Series sensors protect against fake and spoof fingerprints by capturing detailed surface and deep tissue data. Using the biometric industry's best spoof detection technology, we provide the most secure and accurate sensors available over 20,000 samples tested and detected to date.\u003c\/p\u003e\n\n\u003ch3\u003eEase of Integration\u003c\/h3\u003e\n\u003cp\u003eLumidigm's V-Series sensors are small, lightweight sensors equipped with multiple communication interfaces that easily integrate with existing systems. Designed for this ease of integration*, Lumidigm sensors rise to the top with accurate, high-quality images and solve your performance problems, anytime, anywhere.\u003c\/p\u003e\n\n\u003ch3\u003eState-of-the-Art Performance\u003c\/h3\u003e\n\u003cp\u003eV-Series sensors outperform other sensors by improving your application's throughput, accuracy, speed, and security. Let Lumidigm's patented technology solve your management hassles and end-user frustration by delivering the high-quality images you expect every time.\u003c\/p\u003e\n\n\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003ctable class=\"\" data style=\"\" cellspacing=\"\" cellpadding=\"\" border=\"\" bgcolor=\"#FFFFFF\" width:=\"\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd class=\"\" cap_left style=\"\" width: font-weight: bold bgcolor=\"f4f4f4\"\u003eDevice name\u003c\/td\u003e\n\u003ctd style=\"\" text-align: left width=\"\"\u003eV-Series V311\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"\" cap_left style=\"\" font-weight: bold bgcolor=\"f4f4f4\"\u003eManufacturer\u003c\/td\u003e\n\u003ctd style=\"\" text-align: left\u003e Lumidigm, Inc. \u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"\" cap_left style=\"\" font-weight: bold bgcolor=\"f4f4f4\"\u003eDevice connection\u003c\/td\u003e\n\u003ctd style=\"\" text-align: left\u003eUSB 2.0\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"\" cap_left style=\"\" font-weight: bold bgcolor=\"f4f4f4\"\u003eSupported OS \u003csup\u003e(1)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003ctd style=\"\" text-align: left\u003eMicrosoft Windows (32bit and 64bit)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"\" cap_left style=\"\" font-weight: bold bgcolor=\"f4f4f4\"\u003eSensor resolution\u003c\/td\u003e\n\u003ctd style=\"\" text-align: left\u003e500 dpi\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"\" cap_left style=\"\" font-weight: bold bgcolor=\"f4f4f4\"\u003eImage capture area (Platen size)\u003c\/td\u003e\n\u003ctd style=\"\" text-align: left\u003e18 x 28 mm (0.7\"\" x 1.1\"\")\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"\" cap_left style=\"\" font-weight: bold bgcolor=\"f4f4f4\"\u003eFingerprint capture method\u003c\/td\u003e\n\u003ctd style=\"\" text-align: left\u003eTouch\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"\" cap_left style=\"\" font-weight: bold bgcolor=\"f4f4f4\"\u003eSensor type\u003c\/td\u003e\n\u003ctd style=\"\" text-align: left\u003eOptical\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"\" cap_left style=\"\" font-weight: bold bgcolor=\"f4f4f4\"\u003eIllumination\u003c\/td\u003e\n\u003ctd style=\"\" text-align: left\u003eMultispectral\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"\" cap_left style=\"\" font-weight: bold bgcolor=\"f4f4f4\"\u003eDevice size\u003c\/td\u003e\n\u003ctd style=\"\" text-align: left\u003e83 x 100 x 59 mm (3.3\"\" x 4.0\"\" x 2.3\"\")\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"\" cap_left style=\"\" font-weight: bold bgcolor=\"f4f4f4\"\u003eOperating temperature\u003c\/td\u003e\n\u003ctd style=\"\" text-align: left\u003e-10°C ~ +50°C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"\" cap_left style=\"\" font-weight: bold bgcolor=\"f4f4f4\"\u003eOperating humidity\u003c\/td\u003e\n\u003ctd style=\"\" text-align: left\u003e0-100% condensing\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\n\u003ch2\u003eProduct Compatibility\u003c\/h2\u003e\n\u003cp\u003eThe Lumidigm V-Series Readers are compatible with many different software development kits and applications.  Below is the list of products that are currently known to support this scanner.  Please note that some applications and development kits require specific versions of the drivers to be installed. Please contact us if you need additional information.\u003c\/p\u003e\n\n\u003ch3\u003eSupported Software Development Kits:\u003c\/h3\u003e\n\u003cp\u003eVeriFinger Standard and Extended SDK\u003c\/p\u003e\n\u003cp\u003eMegaMatcher Standard and Extended SDK\u003c\/p\u003e\n\n\u003ch3\u003eSupported Applications:\u003c\/h3\u003e\n\u003cp\u003eFbF\u003csup\u003e(TM)\u003c\/sup\u003e Device Listener\u003c\/p\u003e","brand":"Crossmatch\/ HID Global","offers":[{"title":"Default Title","offer_id":41331018072166,"sku":"101171","price":392.52,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/101170-2-min_7a937583-ec89-4784-873f-59f1e5ab884d.jpg?v=1714422349"},{"product_id":"lumidigm-v-series-v371-fingerprint-sensor","title":"Lumidigm V-Series V371 Fingerprint Sensor","description":"\u003cp\u003eThe Lumidigm V371 Fingerprint Reader combines the industry-leading biometric authentication of HID Global's multispectral fingerprint sensors and best-in-class contactless OMNIKEY® desktop card-reading technology into a single, integrated unit for strong multi-factor authentication.\u003c\/p\u003e\n\u003cp\u003eSometimes it's enough to validate a card; sometimes knowing 'who' is critical. Whatever authentication policy is employed, HID Global's Lumidigm V371 Fingerprint Reader allows easy verification of contactless cards and fingerprint biometrics on a single device.\u003c\/p\u003e\n\u003cp\u003eThe solution provides reliable, convenient and secure method for authenticating both a credential and the individual presenting it. The Lumidigm V371 Fingerprint Reader is ideal for applications leveraging biometric citizen ID cards.\u003c\/p\u003e\n\u003ch3\u003eKey Benefits\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003eSecure and Convenient - Provides reliable biometric authentication information that can be used to verify the identity of anyone, anytime. Simply place a card in the cradle and a finger on the plate and legitimate users can be on their way.\u003c\/li\u003e\n\u003cli\u003eEliminates Fraud - Multi-factor solution protects against fake fingerprints and detects the use of shared or stolen ID cards.\u003c\/li\u003e\n\u003cli\u003eReal Identity Verification - Augment existing credentials with a biometric enrollment for multi-factor verification of the user and their card.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003eWatch a video on the Lumidigm V-Series V371 Fingerprint Sensor on YouTube\u003c\/p\u003e\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003ch3\u003eFINGERPRINT IMAGING SYSTEM\u003c\/h3\u003e\n\u003ctable bgcolor=\"#FFFFFF\" border=\"\" cellpadding=\"\" cellspacing=\"\" width:=\"\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eTechnology\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eV-Series V302\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eImage resolution \/ bit depth\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003e500 dpi \/ 8-bit, 256 grayscale\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003ePlaten area\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003e0.7\" x 1.1\" (18mm x 28mm) ellipse\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003ch3\u003eBIOMETRIC FUNCTIONS\u003c\/h3\u003e\n\u003ctable bgcolor=\"#FFFFFF\" border=\"\" cellpadding=\"\" cellspacing=\"\" width:=\"\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eImage out\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eANSI 381 compliant, ISO 19794-4:2011, FBI certified WSQ, Flat Binary\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eTemplate out\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eUses ANSI 378+ templates as input\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eScore or verification (1:1)\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eRequires ANSI 378 template input\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eIdentification (1:N)\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eUses ANSI 3 78+ t empla tes as input\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eLiveness detection\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eIncluded\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eLatent protection\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eIncluded\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003ch3\u003eFINGERPRINT TEMPLATE STORAGE\u003c\/h3\u003e\n\u003ctable bgcolor=\"#FFFFFF\" border=\"\" cellpadding=\"\" cellspacing=\"\" width:=\"\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eVerification (1:1)\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003en\/a on device; unlimited on PC\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eIdentification (1:N)\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eUp to 5000 users on USB host (SDK 6+); up to 1000 users per group, unlimited groups (SDK 5) Note: 1:N templates not compatible between SDK 5 and SDK 6\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003ch3\u003eCARD READING SYSTEM\u003c\/h3\u003e\n\u003ctable bgcolor=\"#FFFFFF\" border=\"\" cellpadding=\"\" cellspacing=\"\" width:=\"\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eContactless card interfacE\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003e13.56 MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eSupported smartcards\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eISO14443A\/B ISO156 93\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eSupported credentials\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eMIFARE® Classic, MIFARE DESFire® 0.6, and MIFARE DESFire EV1 contactless cards\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eTransmission rate\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eUp to 848 kb\/s\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003ch3\u003eENVIRONMENTAL RANGE\u003c\/h3\u003e\n\u003ctable bgcolor=\"#FFFFFF\" border=\"\" cellpadding=\"\" cellspacing=\"\" width:=\"\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eIngress protection\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eIP65 at the platen \/ IP53 enclosure\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eOperating temperature\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003e0 to 60°C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eStorage temperature\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003e-20 to 80°C\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eESD Immunity\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eIEC 61000-4-2 4kV\/8kV\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003ch3\u003eINTERFACE\u003c\/h3\u003e\n\u003ctable bgcolor=\"#FFFFFF\" border=\"\" cellpadding=\"\" cellspacing=\"\" width:=\"\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eUSB\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eHigh-speed USB 2.0 Bus Powered\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eIndicator Lights\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eBlue \/ Green \/ Red\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eOperating Systems Supported\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eWindows 10 (32b\/64b); Windows 8 (32b\/64b); Windows 7 (32b\/64b); Windows XP\/2000 (Deprecated)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eEncryption\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eEncrypted video for privacy\/playback protectio\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003ch3\u003eFORM FACTOR\u003c\/h3\u003e\n\u003ctable bgcolor=\"#FFFFFF\" border=\"\" cellpadding=\"\" cellspacing=\"\" width:=\"\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eOverall Dimensions\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003e79.2 mm x 124.3 mm x 63.2 mm (3.12\"\" x 4.89\"\" x 2.49\"\")\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eHousing\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003ePlastic, IP53\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003ch3\u003ePOWER SUPPLY REQUIREMENTS\u003c\/h3\u003e\n\u003ctable bgcolor=\"#FFFFFF\" border=\"\" cellpadding=\"\" cellspacing=\"\" width:=\"\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eSupply current - operational\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003e+5 VDC 500 mA (peak)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eSupply current idle\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003e+5 VDC 250 mA (typical)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003ch3\u003eSTANDARDS COMPLIANCE\u003c\/h3\u003e\n\u003ctable bgcolor=\"#FFFFFF\" border=\"\" cellpadding=\"\" cellspacing=\"\" width:=\"\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eInteroperability\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eANSI 378, ISO 19794-2:2011, ANSI 381, ISO 19794-4:2011, NFIQ compliant, MINEX III-certified algorithm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eDevice certifications\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eCE, FCC Part 15 Subpart C, RSS Gen, RSS 210, R\u0026amp;TTE Directive including EN 300 330, EN 301 489, RoHS, DEA, EPCS, Microsoft WHQL\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003ch3\u003eMINIMUM SYSTEM REQUIREMENTS\u003c\/h3\u003e\n\u003ctable bgcolor=\"#FFFFFF\" border=\"\" cellpadding=\"\" cellspacing=\"\" width:=\"\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eInterface\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eHigh-speed USB 2.0 (480 Mbps\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eMemory\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003e64 MB free RAM\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd bgcolor=\"f4f4f4\" class=\"\" font-weight:=\"\" width:=\"\"\u003eOperating System\u003c\/td\u003e\n\u003ctd width=\"\" text-align:=\"\"\u003eSupported OS required (see Interface)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e","brand":"Crossmatch\/ HID Global","offers":[{"title":"Default Title","offer_id":41331018170470,"sku":"101187","price":466.89,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/101187-2-min.jpg?v=1714422351"},{"product_id":"m321-lumidigm-m-series-fingerprint-sensor","title":"Lumidigm M-Series M321 Fingerprint Sensor","description":"\u003cp\u003eEnhanced fingerprint capture firmware and high-performing liveness detection available in the embedded M321! \u003c\/p\u003e\n\n\u003ch2\u003eFeatures\u003c\/h2\u003e\n\u003cul\u003e\n\t\u003cli\u003eReal World Performance - Patented Lumidigm multispectral imaging outperforms conventional fingerprint technologies, reducing problems with user enrollment and matching. \u003c\/li\u003e\n\t\u003cli\u003eReliable Fingerprint Capture - Enhanced finger detection software consistently captures high quality fingerprint images from all users in all environments. \u003c\/li\u003e\n\t\u003cli\u003eHigh-Performance Liveness Detection - Embedded sensors now provide strong liveness detection, preventing the fraudulent use of fake or stolen biometric data. \u003c\/li\u003e\n\t\u003cli\u003eEnhanced Matching - Top-ranked MINEX III algorithm is interoperable with ANSI\/ISO templates and delivers accurate 1:1 matching and 1:N searches up to 5,000 users. \u003c\/li\u003e\n\t\u003cli\u003eExcellent Value - Robust, compact and field-proven, M-Series USB sensors bring multispectral imaging to the enterprise desktop.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\n\tLumidigm M-Series Fingerprint Sensors extend patented multispectral imaging technology to the value-conscious enterprise, providing the required durability and performance in a sleek and compact USB desktop housing. The M-Series captures fingerprint data for all users, detects fraudulent verification attempts, and provides accurate fingerprint matching. With the M-Series, you can strengthen your identity and access management solution by replacing vulnerable passwords with the quick and secure touch of a finger.\n\u003c\/p\u003e\n\u003cp\u003e\n\tMultispectral imaging technology captures surface and subsurface fingerprint data, delivering clear images every time, even when finger surface features are hard to distinguish due to age, dryness, or finger pressure. Multispectral imaging outperforms traditional optical or capacitive technologies that capture only surface details, resulting in poor performance in common conditions.\n\u003c\/p\u003e\n\u003cp\u003e\n\tHigh-performance liveness detection, available with the M321, prevents the fraudulent use of fake or stolen biometric data and protects user privacy.\n\u003c\/p\u003e\n\u003cp\u003e\n\tThe M Series features a top ranked MINEX III certified algorithm with interoperable ANSI\/ISO fingerprint minutia templates, proven 1:1 and 1:N matching up to 5000 users, and FBI-certified WSQ finger image compression. The desktop devices support image, template and match score outputs and are available in embedded or streaming operating mode.\n\u003c\/p\u003e\n\u003cp\u003e\n\tThe M-Series USB sensors are ideal desktop devices to replace passwords and prevent the use of shared, stolen or faked ID credentials in logical access applications such as employee network access (single sign-on), bank teller authentication, patient and healthcare provider authentication, and point of sale (POS) transactions.\n\u003c\/p\u003e\n\u003ch4\u003eUse Cases\u003c\/h4\u003e\n\u003cul\u003e\n\t\u003cli\u003eEnterprise: Logical access  \u003c\/li\u003e\n\t\u003cli\u003eBanking: Employee logical access (single sign-on), teller authentication  \u003c\/li\u003e\n\t\u003cli\u003eHealthcare: Patient and staff authentication, electronic medical record access, e-prescribing (EPCS)  \u003c\/li\u003e\n\t\u003cli\u003ePoint of Sale (POS)  \u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch4\u003eKey Enhancements\u003c\/h4\u003e\n\u003cul\u003e\n\t\u003cli\u003eMore reliable fingerprint image capture\u003c\/li\u003e\n\t\u003cli\u003eHigh performance liveness detection  \u003c\/li\u003e\n\t\u003cli\u003eTop MINEX III algorithm for improved 1:1 and 1:N matching up to 5000   \u003c\/li\u003e\n\t\u003cli\u003eUpdated SDK tools  \u003c\/li\u003e\n\u003c\/ul\u003e\n\n\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003ctable style=\"\" cellspacing=\"\" cellpadding=\"\" border=\"\" bgcolor=\"#FFFFFF\" width:=\"\"\u003e\n\u003ctbody\u003e\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tTechnology \n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t\tPatented Lumidigm optical multispectral imaging  \n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tImage resolution \/ bit depth\n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n500 dpi \/ 8-bit, 256 grayscale\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tPlaten area \n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t\t0.55\" x .69\" (13.9mm x 17.4mm) rectangle, uncoated\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\n\u003ch2\u003eBiometric Functions\u003c\/h2\u003e\n\u003ctable style=\"\" cellspacing=\"\" cellpadding=\"\" border=\"\" bgcolor=\"#FFFFFF\" width:=\"\"\u003e\n\n\u003ctbody\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"\" vertical-align: top font-weight: bold bgcolor=\"f4f4f4\"\u003e\n\t\tImage output format\u003cbr\u003e\n\t\u003c\/td\u003e\n\t\u003ctd style=\"\" vertical-align: top\u003e\n\t\tANSI 381, ISO 19794-4,\nWSQ compression (FBI certified)\u003cbr\u003e\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\n\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tTemplate output format\n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t1:1: ANSI 378, ISO 19794-2\n1:N: Proprietary (ANSI 378+ format) \n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tVerify (1:1) match score input \n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t\t \t \tANSI 378 or ISO 19794-2 input  \n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tIdentify (1:N) search score input\n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\tProprietary template (ANSI 378+ format)\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tLatent and liveness detection\n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t\t \t \tYes\n\t\u003c\/td\u003e\n\t\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\t\n\u003ch2\u003eBiometric Processing Times\u003c\/h2\u003e\n\u003ctable style=\"\" cellspacing=\"\" cellpadding=\"\" border=\"\" bgcolor=\"#FFFFFF\" width:=\"\"\u003e\n\n\u003ctbody\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"\" vertical-align: top font-weight: bold bgcolor=\"f4f4f4\"\u003e\n\t\tFinger touch to image capture\u003cbr\u003e\n\t\u003c\/td\u003e\n\t\u003ctd style=\"\" vertical-align: top\u003e\n\t\t200 ms (typical)\u003cbr\u003e\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\n\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tFinger touch to image out\n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t\t1.1 sec (typical) \n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tFinger touch to 1:1 score or template\n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t\t \t 1.6 sec (typical)\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tFinger touch to 1:N score\n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t\t \t2.0 sec (typical, 1,000 users)\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tLiveness detection (when enabled)\n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t\t \t425 ms (added processing time)\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eEnvironmental Range\u003c\/h2\u003e\n\u003ctable style=\"\" cellspacing=\"\" cellpadding=\"\" border=\"\" bgcolor=\"#FFFFFF\" width:=\"\"\u003e\n\n\u003ctbody\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"\" vertical-align: top font-weight: bold bgcolor=\"f4f4f4\"\u003e\n\t\tIngress protection\u003cbr\u003e\n\t\u003c\/td\u003e\n\t\u003ctd style=\"\" vertical-align: top\u003e\n\t\tIP50 dust and water protection\u003cbr\u003e\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\n\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tAmbient light tolerance\n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t\t90 Klux (liveness off), 10 Klux (liveness on)\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tTemperature (operating)\n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t\t \t -10 to 60°C\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tHumidity (operating)\n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t\t \t0-100% RH condensing\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tESD immunity (operating)\n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t\t \tIEC 61000-4-2 Level 3 +\/-8 kV air discharge\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eInterface\u003c\/h2\u003e\n\u003ctable style=\"\" cellspacing=\"\" cellpadding=\"\" border=\"\" bgcolor=\"#FFFFFF\" width:=\"\"\u003e\n\n\u003ctbody\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"\" vertical-align: top font-weight: bold bgcolor=\"f4f4f4\"\u003e\n\t\tDevice Interface\u003cbr\u003e\n\t\u003c\/td\u003e\n\t\u003ctd style=\"\" vertical-align: top\u003e\n\t\tUSB 1.1 or 2.0\u003cbr\u003e\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\n\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tMemory, platform requirement\n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t\tn\/a\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tOperating systems supported\n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t\t \t Windows 10\/8\/7 (32b\/64b), Windows XP, Linux, Android (M321 or M301 only)\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tEncryption\n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t\t \tn\/a\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eForm Factor\u003c\/h2\u003e\n\u003ctable style=\"\" cellspacing=\"\" cellpadding=\"\" border=\"\" bgcolor=\"#FFFFFF\" width:=\"\"\u003e\n\n\u003ctbody\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"\" vertical-align: top font-weight: bold bgcolor=\"f4f4f4\"\u003e\n\t\tOverall dimensions\u003cbr\u003e\n\t\u003c\/td\u003e\n\t\u003ctd style=\"\" vertical-align: top\u003e\n\t1.9W x 3.1D x 2.0H (47mm x 78mm x 52mm)\u003cbr\u003e\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\n\n\u003ctr valign=\"\" top\u003e\n\t\u003ctd style=\"\" font-weight: bold width=\"\" bgcolor=\"f4f4f4\"\u003e\n\t\tHousing\n\t\u003c\/td\u003e\n\t\u003ctd width=\"\"\u003e\n\t\tABS plastic\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003ePower Supply Requirements\u003c\/h2\u003e\n\u003ctable style=\"\" cellspacing=\"\" cellpadding=\"\" border=\"\" bgcolor=\"#FFFFFF\" width:=\"\"\u003e\n\n\u003ctbody\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"\" vertical-align: top font-weight: bold bgcolor=\"f4f4f4\"\u003e\n\t\t+5VDC Current: Operational \/ Idle\u003cbr\u003e\n\t\u003c\/td\u003e\n\t\u003ctd style=\"\" vertical-align: top\u003e\n\t400 mA Operational (peak) \/ 200 mA Idle (typical)\u003cbr\u003e\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eStandards Compliance\u003c\/h2\u003e\n\u003ctable style=\"\" cellspacing=\"\" cellpadding=\"\" border=\"\" bgcolor=\"#FFFFFF\" width:=\"\"\u003e\n\n\u003ctbody\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"\" vertical-align: top font-weight: bold bgcolor=\"f4f4f4\"\u003e\n\t\tInteroperability\u003cbr\u003e\n\t\u003c\/td\u003e\n\t\u003ctd style=\"\" vertical-align: top\u003e\n\tMINEX III, ANSI 378, ISO 19794-2:2011,\nANSI 381, ISO 19794-4:2011, NFIQ, WSQ\u003cbr\u003e\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\t\u003ctd style=\"\" vertical-align: top font-weight: bold bgcolor=\"f4f4f4\"\u003e\n\t\tDevice certifications\u003cbr\u003e\n\t\u003c\/td\u003e\n\t\u003ctd style=\"\" vertical-align: top\u003e\n\tCE, FCC Part 15 Class B, EN 60950, IEC 62471, RoHS, DEA EPCS, support for thin clients\u003cbr\u003e\n\t\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e","brand":"Crossmatch\/ HID Global","offers":[{"title":"Default Title","offer_id":41331018367078,"sku":"101199","price":225.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/101174-3-min_2c97c283-06cc-4706-bb92-410f20972cb4.jpg?v=1714422354"},{"product_id":"megamatcher-extended-sdk","title":"MegaMatcher Extended SDK","description":"\u003ch2\u003eLarge Scale AFIS and multi-biometric identification\u003cbr\u003e\n\u003c\/h2\u003e\n\u003cp\u003eMegaMatcher is designed for large-scale AFIS and multi-biometric systems developers. The technology ensures high reliability and speed of biometric identification even when using large databases.\u003c\/p\u003e\n\u003cp\u003eAvailable as a software development kit that allows development of large-scale single- or multi-biometric fingerprint, iris, face, voice or palm print identification products for Microsoft Windows, Linux, Mac OS X, iOS and Android platforms.\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eMegaMatcher 11.0 Extended SDK\u003c\/b\u003e or developing a large-scale network-based AFIS or multi-biometric identification product. The SDK includes all components of MegaMatcher 11.0 Standard SDK and MegaMatcher Accelerator software, which can be used for fault-tolerant scalable cluster software for fast parallel matching, processing high number of identification requests and handling databases with practically unlimited size. This SDK also allows to develop network-based and web-based systems.\u003c\/p\u003e\n\u003ch3\u003eFeatures \u0026amp; Capabilities\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003eProven in national-scale projects, including passport issuance and voter deduplication.\u003c\/li\u003e\n\u003cli\u003eNIST MINEX-compliant fingerprint engine, NIST IREX proven iris engine.\u003c\/li\u003e\n\u003cli\u003eTurnkey multi-biometric solution for national-scale identification projects with MegaMatcher ABIS.\u003c\/li\u003e\n\u003cli\u003eHigh performance matching for large-scale systems with MegaMatcher Accelerator.\u003c\/li\u003e\n\u003cli\u003eFingerprints, irises and faces can be matched on smart cards using MegaMatcher On Card.\u003c\/li\u003e\n\u003cli\u003eIncludes fingerprint, iris, face, voice and palm print modalities.\u003c\/li\u003e\n\u003cli\u003eRolled, flat and latent fingerprint matching.\u003c\/li\u003e\n\u003cli\u003eBioAPI 2.0 and other ANSI and ISO biometric standards support.\u003c\/li\u003e\n\u003cli\u003eICAO requirements compliancy check for face images.\u003c\/li\u003e\n\u003cli\u003eEffective price\/performance ratio, flexible licensing and free customer support.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eSDK contents\u003c\/h2\u003e\n\u003cp\u003eMegaMatcher SDK is designed for development of large-scale AFIS or multi-biometric identification products. Fingerprint, face, iris, voice and palm print recognition engines are included in MegaMatcher 11.0 SDK.\u003c\/p\u003e\n\u003cp\u003eMegaMatcher 11.0 SDK includes server-side software and a set of modules for developing client-side applications. .NET components are included for rapid development of client-side software. MegaMatcher 11.0 supports \u003cb\u003eBioAPI 2.0.\u003c\/b\u003e To ensure system compatibility with other software, WSQ component is available, as well as modules for conversion between MegaMatcher template and biometric standards.\u003c\/p\u003e\n\u003cp\u003eMegaMatcher 11.0 is suitable not only for developing \u003cb\u003ecivil AFIS\u003c\/b\u003e, but also for \u003cb\u003eforensic AFIS applications,\u003c\/b\u003e as it includes an API for \u003cb\u003elatent fingerprint template editing.\u003c\/b\u003e Latent fingerprint template editing is necessary in order to submit a latent fingerprint (for example, one taken from a crime scene) for the identification into AFIS. Also, MegaMatcher is able to \u003cb\u003ematch rolled and flat fingerprints between themselves. \u003c\/b\u003e\u003c\/p\u003e\n\u003cp\u003eThe table below compares MegaMatcher 11.0 Standard SDK and MegaMatcher 11.0 Extended SDK components.\u003c\/p\u003e\n\u003cdiv align=\"center\"\u003e\n\u003ctable class=\"data\" width=\"100%\" cellspacing=\"0\" cellpadding=\"0\" border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" width=\"50%\" valign=\"bottom\"\u003eComponent types\u003c\/td\u003e\n\u003ctd class=\"cap_top\" width=\"25%\"\u003eMegaMatcher 11.0\u003cbr\u003eStandard SDK\u003c\/td\u003e\n\u003ctd class=\"cap_top\" width=\"25%\"\u003eMegaMatcher 11.0 Extended SDK\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth colspan=\"3\"\u003eFingerprint component licenses included with a specific SDK:\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Fingerprint Image Processing\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Fast Fingerprint Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Fingerprint Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Fingerprint Extractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Fingerprint Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Fingerprint Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Fingerprint Extractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Fingerprint Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth colspan=\"3\"\u003eFace component licenses included with a specific SDK:\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Face Image Processing\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Fast Face Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Face Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Face Extractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Face Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Face Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Face Extractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Face Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth colspan=\"3\"\u003eIris component licenses included with a specific SDK:\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Iris Image Processing\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Fast Iris Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Iris Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Iris Extractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Iris Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Iris Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Iris Extractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Iris Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth colspan=\"3\"\u003eVoice component licenses included with a specific SDK:\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Voice Processing\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Voice Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Voice Extractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Voice Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Voice Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Voice Extractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Voice Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth colspan=\"3\"\u003ePalm print component licenses included with a specific SDK:\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Palm Print Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Palm Print Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth colspan=\"3\"\u003eServer-side matching component licenses included with a specific SDK:\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Matching Server\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• MegaMatcher Accelerator 11.0 Development Edition fingerprint, face and iris engines license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e\u003cbr\u003e\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003c\/div\u003e\n\u003ch3\u003eMegaMatcher Fingerprint Template Extraction and Matching Engine\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cb\u003eFull MINEX Compliance.\u003c\/b\u003e NIST has recognized MegaMatcher fingerprint algorithm as MINEX compliant and suitable for use in personal identity verification (PIV) program applications.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eRolled and flat fingerprints matching.\u003c\/b\u003e The MegaMatcher fingerprint engine matches rolled and flat fingerprints \u003cb\u003ebetween themselves. \u003c\/b\u003eTypically, conventional \"flat\" fingerprint identification algorithms perform matching between flat and rolled fingerprints less reliably due to the specific deformations of rolled fingerprints. MegaMatcher allows flat-to-flat, flat-to-rolled or rolled-to-rolled fingerprint matching with a high degree of reliability and accuracy. The algorithm matches up to 200,000 flat fingerprint records per second on a single PC.\u003c\/li\u003e\n\u003cli\u003eMegaMatcher includes fingerprint \u003cb\u003eimage quality determination\u003c\/b\u003e, which may be used during enrollment to ensure that only the best quality fingerprint template will be stored in the database.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eTemplate generalization\u003c\/b\u003e is used to generate a better quality template from several fingerprints. Better quality templates result in a higher level of identification accuracy.\u003c\/li\u003e\n\u003cli\u003eMegaMatcher is\u003cb\u003e tolerant to fingerprint translation, rotation and deformation.\u003c\/b\u003e It uses a proprietary fingerprint matching algorithm that identifies fingerprints even if they are rotated, translated or have deformations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eAdaptive image filtration \u003c\/b\u003ealgorithm eliminates noises, ridge ruptures and stuck ridges, and reliably extracting minutiae from even the poorest quality fingerprints in less than 1 second.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eMegaMatcher Face Template Extraction and Matching Engine\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cb\u003eTemplate generalization\u003c\/b\u003e is used to generate a better quality template from several face images. Better quality templates result in a higher level of identification accuracy.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eTolerance to face position\u003c\/b\u003e assures a level of enrollment convenience. MegaMatcher allows for 360 degrees of head roll. Head pitch can be up to 15 degrees in each direction from the frontal position. Head yaw can be up to 45 degrees in each direction from the frontal position. See technical specifications for more details.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eReliable face detection\u003c\/b\u003e assures accurate enrollment from cameras, webcams and various scanned documents; faces may be enrolled from the scanned pages of passports or other types of documentation. When there are \u003cb\u003emultiple faces\u003c\/b\u003e present in a video or an image, they may be enrolled and processed simultaneously. Person's \u003cb\u003egender,\u003c\/b\u003e facial feature points and basic \u003cb\u003eemotions\u003c\/b\u003e can be optionally detected.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eFacial attributes recognition\u003c\/b\u003e. MegaMatcher can be configured to detect certain attributes during the face extraction –\u003cb\u003e smile, open-mouth, closed-eyes, glasses, dark-glasses, beard and mustache.\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eAge estimation.\u003c\/b\u003e MegaMatcher can optionally estimate person's age by analyzing the detected face in the image.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eLive face detection.\u003c\/b\u003e A conventional face identification system can be tricked by placing a photo in front of the camera. MegaMatcher is able to prevent this kind of security breach by determining whether a face in a video stream is \"live\" or a photograph. The liveness detection can be performed in passive mode, when the engine evaluates certain facial features, and in active mode, when the engine evaluates user's response to perform actions like blinking or head movements. See recommendations for live face detection for more details.\u003c\/li\u003e\n\u003cli\u003eThe biometric template record can contain \u003cb\u003eseveral face samples belonging to the same person.\u003c\/b\u003e These samples can be enrolled from different sources and at different times, thus allowing improvement in matching quality. For example a person might be enrolled with eyeglasses and without, or with different types of eyeglasses; with and without beard or mustache, etc.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eMegaMatcher Voice Template Extraction and Matching Engine\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cb\u003eText-dependent\u003c\/b\u003e voice matching engine determines if a voice sample matches the template that was extracted from a specific phrase. During enrollment, one or more phrases are requested from the person being enrolled. Later that person may be asked to pronounce a specific phrase for verification. This method assures protection against the use of a covertly recorded random phrase from that person.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eTwo-factor authentication with a passphrase\u003c\/b\u003e is performed when a person is asked to say a \u003cb\u003eunique phrase\u003c\/b\u003e (such as passphrase or an answer to a \"secret question\" that is \u003cb\u003eknown only by the person\u003c\/b\u003e being enrolled). The overall system security increases as both voice authenticity and password are checked.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eText-independent \u003c\/b\u003evoice matching engine uses different phrases for user enrollment and recognition. This method is more convenient, as it does not require each user to remember the passphrase. It may be combined with the text-dependent algorithm to perform faster text-independent search with further phrase verification using the more reliable text-dependent algorithm.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eAutomatic voice activity detection.\u003c\/b\u003e The engine is able to detect when users start and finish speaking.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eLiveness detection.\u003c\/b\u003e A system may request each user to enroll a set of unique phrases. Later the user will be requested to say a specific phrase from the enrolled set. This way the system can ensure that a live person is being verified (as opposed to impostor who uses voice recording).\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eSeveral voice records with the same phrase\u003c\/b\u003e may be stored to improve speaker recognition reliability. Certain natural voice variations (i.e. hoarse voice) or environment changes (i.e. office and outdoors) can be stored in the same template.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eMegaMatcher Iris Template Extraction and Matching Engine\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cb\u003eNIST IREX proven reliability.\u003c\/b\u003e MegaMatcher iris matching engine is based on VeriEye, recognized by NIST as one of the most reliably accurate iris recognition algorithms available.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eFast matching.\u003c\/b\u003e The iris matching speed is up to\u003cb\u003e 200,000 comparisons per second\u003c\/b\u003e on a single PC. See technical specifications for more details.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eRobust iris detection.\u003c\/b\u003e Irises are detected even when there are obstructions to the image, visual noise and\/or different levels of illumination. Lighting reflections, eyelids and eyelashes obstructions are eliminated. Images with narrowed eyelids or eyes that are gazing away are also accepted.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eAutomatic interlacing detection and correction\u003c\/b\u003e results in maximum quality of iris feature templates from moving iris images.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eCorrect iris segmentation\u003c\/b\u003e is obtained even when perfect circles fail, the centers of the iris inner and outer boundaries are different, iris boundaries are definitely not circles and even not ellipses or iris boundaries seem to be perfect circles.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eIris image quality determination and spoof prevention.\u003c\/b\u003e The image quality estimation can be used during iris enrollment to ensure that only the best quality iris template will be stored into database. Also, cosmetic (decorative) contact lens, which obscure an iris with some artistic or \u003cb\u003efake iris texture\u003c\/b\u003e and\/or change iris color, can be detected.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003cp\u003eAll biometric templates should be loaded into RAM before identification, thus the maximum biometric templates database size is limited by the amount of available RAM.\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eFingerprint scanners are recommended to have at least \u003cstrong\u003e500 ppi\u003c\/strong\u003e resolution and at least \u003cstrong\u003e1\" x 1\"\u003c\/strong\u003e fingerprint sensors. The specifications are provided for 500 x 500 pixels fingerprint images and templates extracted from these images.\u003c\/li\u003e\n\u003cli\u003eThe \u003cstrong\u003eminimal distance between eyes is 32 pixels\u003c\/strong\u003e for a face on image or video stream to perform face template extraction reliably. \u003cstrong\u003e64 pixels or more recommended\u003c\/strong\u003e for better template extraction results.\u003c\/li\u003e\n\u003cli\u003eFace recognition engine has certain tolerance to face posture:\n\u003cul class=\"complex\"\u003e\n\u003cli\u003ehead \u003cstrong\u003eroll\u003c\/strong\u003e (tilt) – ±180 degrees (configurable); \u003cbr\u003e \u003cstrong\u003e±15 degrees default\u003c\/strong\u003e value is the fastest setting which is usually sufficient for most near-frontal face images.\u003c\/li\u003e\n\u003cli\u003ehead \u003cstrong\u003epitch\u003c\/strong\u003e (nod) – ±15 degrees from frontal position.\u003c\/li\u003e\n\u003cli\u003ehead \u003cstrong\u003eyaw\u003c\/strong\u003e (bobble) – ±45 degrees from frontal position. \u003cbr\u003e \u003cstrong\u003e±15 degrees default\u003c\/strong\u003e value is the fastest setting which is usually sufficient for most near-frontal face images.\u003c\/li\u003e\n\u003c\/ul\u003e\nThe specifications are provided for the default roll and yaw values.\u003c\/li\u003e\n\u003cli\u003eIris capture cameras are recommended to produce at least \u003cstrong\u003e640 x 480 pixels\u003c\/strong\u003e images. The specifications are provided for these images.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eVoice samples of at least 2-seconds in length are recommended\u003c\/strong\u003e to assure speaker recognition quality.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eA minimum 11025 Hz\u003c\/strong\u003e sampling rate, with at least \u003cstrong\u003e16-bit\u003c\/strong\u003e depth, should be used during voice recording.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003eSee also the lists of \u003cstrong\u003ebasic recommendations\u003c\/strong\u003e for facial recognition and speaker recognition.\u003c\/p\u003e\n\u003cp\u003eMegaMatcher biometric template extraction and matching algorithm is designed to run on \u003cstrong\u003emulti-core processors\u003c\/strong\u003e allowing to reach maximum possible performance on the used hardware.\u003c\/p\u003e\n\u003cdiv align=\"center\"\u003e\n\u003ctable style=\"background-color: #ffffff;\" class=\"data\" width=\"100%\" cellspacing=\"0\" cellpadding=\"0\" border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth colspan=\"6\"\u003eMegaMatcher 11.0 fingerprint engine specifications\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_top\"\u003e\u003cbr\u003e\u003c\/td\u003e\n\u003ctd class=\"cap_top\" colspan=\"2\"\u003e\n\u003cspan style=\"font-size: 90%;\"\u003eEmbedded \/ mobile\u003c\/span\u003e \u003csup\u003e(1)\u003c\/sup\u003e\u003cbr\u003eplatform\u003c\/td\u003e\n\u003ctd class=\"cap_top\" colspan=\"2\"\u003ePC-based \u003csup\u003e(2)\u003c\/sup\u003e\u003cbr\u003eplatform\u003c\/td\u003e\n\u003ctd class=\"cap_top\"\u003eServer \u003cbr\u003eplatform\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" width=\"38%\"\u003eTemplate extraction components\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eMobile \u003cbr\u003eFingerprint\u003cbr\u003eExtractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eMobile \u003cbr\u003eFingerprint\u003cbr\u003eClient\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eFingerprint \u003cbr\u003eExtractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eFingerprint \u003cbr\u003eClient\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"14%\"\u003eFingerprint\u003cbr\u003e Image Processing\u003csup\u003e(2)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTemplate extraction speed \u003cbr\u003e(fingerprints per minute)\u003c\/td\u003e\n\u003ctd\u003e45\u003c\/td\u003e\n\u003ctd\u003e50\u003c\/td\u003e\n\u003ctd\u003e45\u003c\/td\u003e\n\u003ctd\u003e100\u003c\/td\u003e\n\u003ctd\u003e3,000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"border-top: solid 2px #CCC;\"\u003eTemplate matching components\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"1\"\u003eMobile \u003cbr\u003eFingerprint\u003cbr\u003eMatcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"1\"\u003eMobile \u003cbr\u003eFast\u003cbr\u003eFingerprint\u003cbr\u003eMatcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"2\"\u003eFingerprint \u003cbr\u003eMatcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\"\u003eFast \u003cbr\u003eFingerprint\u003cbr\u003e Matcher\u003csup\u003e(2)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTemplate matching speed \u003cbr\u003e(fingerprints per second)\u003c\/td\u003e\n\u003ctd colspan=\"1\"\u003e3,000\u003c\/td\u003e\n\u003ctd colspan=\"1\"\u003e200,000\u003c\/td\u003e\n\u003ctd colspan=\"2\"\u003e40,000\u003c\/td\u003e\n\u003ctd\u003e200,000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"border-top: solid 2px #CCC;\"\u003eSingle fingerprint record size in a template \u003csup\u003e(5)\u003c\/sup\u003e (bytes)\u003c\/td\u003e\n\u003ctd style=\"border-top: solid 2px #CCC;\" colspan=\"5\"\u003e800 - 8,000 \u003cbr\u003e\u003cspan class=\"smaller\"\u003e(configurable)\u003c\/span\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cbr\u003e\n\u003ctable style=\"background-color: #ffffff;\" class=\"data\" width=\"100%\" cellspacing=\"0\" cellpadding=\"0\" border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth colspan=\"6\"\u003eMegaMatcher 11.0 face engine specifications\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_top\"\u003e\u003cbr\u003e\u003c\/td\u003e\n\u003ctd class=\"cap_top\" colspan=\"2\"\u003e\n\u003cspan style=\"font-size: 90%;\"\u003eEmbedded \/ mobile\u003c\/span\u003e \u003csup\u003e(1)\u003c\/sup\u003e\u003cbr\u003eplatform\u003c\/td\u003e\n\u003ctd class=\"cap_top\" colspan=\"2\"\u003ePC-based \u003csup\u003e(2)\u003c\/sup\u003e\u003cbr\u003eplatform\u003c\/td\u003e\n\u003ctd class=\"cap_top\"\u003eServer \u003cbr\u003eplatform\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" width=\"38%\"\u003eTemplate extraction components\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eMobile \u003cbr\u003eFace\u003cbr\u003eExtractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eMobile \u003cbr\u003eFace\u003cbr\u003eClient\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eFace \u003cbr\u003eExtractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eFace \u003cbr\u003eClient\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"14%\"\u003eFace \u003cbr\u003e Image Processing\u003csup\u003e(2)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTemplate extraction speed \u003cbr\u003e(faces per minute)\u003c\/td\u003e\n\u003ctd\u003e45\u003c\/td\u003e\n\u003ctd\u003e50\u003c\/td\u003e\n\u003ctd\u003e45\u003c\/td\u003e\n\u003ctd\u003e100\u003c\/td\u003e\n\u003ctd\u003e3,000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"border-top: solid 2px #CCC;\"\u003eTemplate matching components\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"1\"\u003eMobile Face Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"1\"\u003eMobile Fast Face Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"2\"\u003eFace Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\"\u003eFast Face Matcher \u003csup\u003e(2)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTemplate matching speed \u003cbr\u003e(faces per second)\u003c\/td\u003e\n\u003ctd colspan=\"1\"\u003e3,000\u003c\/td\u003e\n\u003ctd colspan=\"1\"\u003e200,000\u003c\/td\u003e\n\u003ctd colspan=\"2\"\u003e40,000\u003c\/td\u003e\n\u003ctd\u003e200,000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"border-top: solid 2px #CCC;\"\u003eSingle face record size in a template \u003csup\u003e(4)\u003c\/sup\u003e (bytes)\u003c\/td\u003e\n\u003ctd style=\"border-top: solid 2px #CCC;\" colspan=\"5\"\u003e194 or 464 \u003cbr\u003e\u003cspan class=\"smaller\"\u003e(configurable)\u003c\/span\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cbr\u003e\n\u003ctable style=\"background-color: #ffffff;\" class=\"data\" width=\"100%\" cellspacing=\"0\" cellpadding=\"0\" border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth colspan=\"6\"\u003eMegaMatcher 11.0 iris engine specifications\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_top\"\u003e\u003cbr\u003e\u003c\/td\u003e\n\u003ctd class=\"cap_top\" colspan=\"2\"\u003e\n\u003cspan style=\"font-size: 90%;\"\u003eEmbedded \/ mobile\u003c\/span\u003e \u003csup\u003e(1)\u003c\/sup\u003e\u003cbr\u003eplatform\u003c\/td\u003e\n\u003ctd class=\"cap_top\" colspan=\"2\"\u003ePC-based \u003csup\u003e(2)\u003c\/sup\u003e\u003cbr\u003eplatform\u003c\/td\u003e\n\u003ctd class=\"cap_top\"\u003eServer \u003cbr\u003eplatform\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" width=\"38%\"\u003eTemplate extraction components\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eMobile \u003cbr\u003eIris\u003cbr\u003eExtractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eMobile \u003cbr\u003eIris\u003cbr\u003eClient\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eIris \u003cbr\u003eExtractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eIris \u003cbr\u003eClient\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"14%\"\u003e\n\u003cp\u003eIris\u003cbr\u003e Image\u003cbr\u003e Processing \u003csup\u003e(2)\u003c\/sup\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTemplate extraction speed \u003cbr\u003e(irises per minute)\u003c\/td\u003e\n\u003ctd\u003e45\u003c\/td\u003e\n\u003ctd\u003e50\u003c\/td\u003e\n\u003ctd\u003e45\u003c\/td\u003e\n\u003ctd\u003e100\u003c\/td\u003e\n\u003ctd\u003e3,000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"border-top: solid 2px #CCC;\"\u003eTemplate matching components\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"1\"\u003eMobile Iris Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"1\"\u003eMobile Fast Iris Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"2\"\u003eIris Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\"\u003eFast Iris Matcher \u003csup\u003e(2)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTemplate matching speed \u003cbr\u003e(irises per second)\u003c\/td\u003e\n\u003ctd colspan=\"1\"\u003e3,000\u003c\/td\u003e\n\u003ctd colspan=\"1\"\u003e200,000\u003c\/td\u003e\n\u003ctd colspan=\"2\"\u003e40,000\u003c\/td\u003e\n\u003ctd\u003e200,000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"border-top: solid 2px #CCC;\"\u003eSingle iris record size in a template \u003csup\u003e(4)\u003c\/sup\u003e (bytes)\u003c\/td\u003e\n\u003ctd style=\"border-top: solid 2px #CCC;\" colspan=\"5\"\u003e2,348\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cbr\u003e\n\u003ctable style=\"background-color: #ffffff;\" class=\"data\" width=\"100%\" cellspacing=\"0\" cellpadding=\"0\" border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth colspan=\"6\"\u003eMegaMatcher 11.0 voiceprint engine specifications\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_top\"\u003e\u003cbr\u003e\u003c\/td\u003e\n\u003ctd class=\"cap_top\" colspan=\"2\"\u003e\n\u003cspan style=\"font-size: 90%;\"\u003eEmbedded \/ mobile\u003c\/span\u003e \u003csup\u003e(1)\u003c\/sup\u003e\u003cbr\u003eplatform\u003c\/td\u003e\n\u003ctd class=\"cap_top\" colspan=\"2\"\u003ePC-based \u003cbr\u003eplatform\u003c\/td\u003e\n\u003ctd class=\"cap_top\"\u003eServer \u003cbr\u003eplatform\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" width=\"38%\"\u003eTemplate extraction components\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eMobile \u003cbr\u003eVoice\u003cbr\u003eExtractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eMobile \u003cbr\u003eVoice\u003cbr\u003eClient\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eVoice \u003cbr\u003eExtractor\u003csup\u003e(2)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eVoice \u003cbr\u003eClient\u003csup\u003e(2)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"14%\"\u003eVoice \u003cbr\u003eProcessing\u003csup\u003e(5)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTemplate extraction speed \u003cbr\u003e(voiceprints per minute)\u003c\/td\u003e\n\u003ctd\u003e45\u003c\/td\u003e\n\u003ctd\u003e50\u003c\/td\u003e\n\u003ctd\u003e45\u003c\/td\u003e\n\u003ctd\u003e100\u003c\/td\u003e\n\u003ctd\u003e3,000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"border-top: solid 2px #CCC;\"\u003eTemplate matching components\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"2\"\u003eMobile Voice Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"3\"\u003eVoice Matcher \u003csup\u003e(2)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTemplate matching speed \u003cbr\u003e(voiceprints per second)\u003c\/td\u003e\n\u003ctd colspan=\"2\"\u003e100\u003c\/td\u003e\n\u003ctd colspan=\"3\"\u003e8,000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"border-top: solid 2px #CCC;\"\u003eSingle voiceprint record size in a template \u003csup\u003e(4)\u003c\/sup\u003e \u003csup\u003e(6)\u003c\/sup\u003e (bytes)\u003c\/td\u003e\n\u003ctd style=\"border-top: solid 2px #CCC;\" colspan=\"5\"\u003e3,500 - 4,500\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003c\/div\u003e\n\u003cp style=\"font-size: 90%;\"\u003eNotes: \u003cbr\u003e (1) Requires to be run on \u003cstrong\u003eiOS\u003c\/strong\u003e devices or \u003cstrong\u003eAndroid\u003c\/strong\u003e devices based on at least \u003cstrong\u003eSnapdragon S4\u003c\/strong\u003e system-on-chip with \u003cstrong\u003eKrait 300\u003c\/strong\u003e processor (4 cores, 1.51 GHz). \u003cbr\u003e (2) Requires to be run on \u003cstrong\u003ePC or laptop\u003c\/strong\u003e with at least Intel \u003cstrong\u003eCore i7-4771\u003c\/strong\u003e quad-core processor (3.5 GHz) to reach the specified performance. \u003cbr\u003e (3) Requires to be run on server hardware with at least \u003cstrong\u003eDual Intel Xeon Gold 6126 processors (2.6 GHz)\u003c\/strong\u003e to reach the specified performance. \u003cbr\u003e (4) MegaMatcher 11.0 allows to store multiple biometric records of the same or different biometric modalities in a template; in this case the template size is the sum of all included biometric records. \u003cbr\u003e (5) Requires to be run on server hardware with at least \u003cb\u003eIntel Xeon Gold 6126 processor (2.6 GHz)\u003c\/b\u003e to reach the specified performance. \u003cbr\u003e(6) The specifications are provided for \u003cb\u003e5-second long voice samples\u003c\/b\u003e; template size has linear dependence from voice sample length.\u003c\/p\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":41331018924134,"sku":"100501","price":4791.75,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/101106-2-min-min.jpg?v=1714422356"},{"product_id":"megamatcher-standard-sdk","title":"MegaMatcher Standard SDK","description":"\u003ch2 data-mce-fragment=\"1\" class=\"title_front\"\u003eLarge Scale AFIS and multi-biometric identification\u003c\/h2\u003e\n\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher is designed for large-scale AFIS and multi-biometric systems developers. The technology ensures high reliability and speed of biometric identification even when using large databases.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eAvailable as a software development kit that allows the development of large-scale single- or multi-biometric fingerprint, iris, face, voice or palm print identification products for Microsoft Windows, Linux, Mac OS X, iOS and Android platforms.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cb data-mce-fragment=\"1\"\u003eMegaMatcher 11.0 Standard SDK\u003c\/b\u003e\u003cspan data-mce-fragment=\"1\"\u003e \u003c\/span\u003eis for developing a client\/server based multi-biometric fingerprint-face-iris identification product. This SDK is suitable for network-based and web-based systems with database sizes ranging from several thousand records up to a million records. The SDK includes ready-to-use server-side software and a set of components for developing client-side applications on Microsoft Windows, Android, iOS, Linux and Mac OS X.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003e\u003cspan\u003eMegaMatcher 11.0 Extended SDK\u003c\/span\u003e\u003cspan\u003e is for developing a large-scale network-based AFIS or multi-biometric identification product. \u003c\/span\u003e\u003c\/p\u003e\n\u003ch3\u003eFeatures \u0026amp; Capabilities\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003eProven in national-scale projects, including passport issuance and voter deduplication.\u003c\/li\u003e\n\u003cli\u003eNIST MINEX-compliant fingerprint engine, NIST IREX proven iris engine.\u003c\/li\u003e\n\u003cli\u003eTurnkey multi-biometric solution for national-scale identification projects with MegaMatcher ABIS.\u003c\/li\u003e\n\u003cli\u003eHigh performance matching for large-scale systems with MegaMatcher Accelerator.\u003c\/li\u003e\n\u003cli\u003eFingerprints, irises and faces can be matched on smart cards using MegaMatcher On Card.\u003c\/li\u003e\n\u003cli\u003eIncludes fingerprint, iris, face, voice and palm print modalities.\u003c\/li\u003e\n\u003cli\u003eRolled, flat and latent fingerprint matching.\u003c\/li\u003e\n\u003cli\u003eBioAPI 2.0 and other ANSI and ISO biometric standards support.\u003c\/li\u003e\n\u003cli\u003eICAO requirements compliancy check for face images.\u003c\/li\u003e\n\u003cli\u003eEffective price\/performance ratio, flexible licensing and free customer support.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eSDK contents\u003c\/h3\u003e\n\u003cp\u003eMegaMatcher SDK is designed for development of large-scale AFIS or multi-biometric identification products. Fingerprint, face, iris, voice and palm print recognition engines are included in MegaMatcher 11.0 SDK.\u003c\/p\u003e\n\u003cp\u003eMegaMatcher 11.0 SDK includes server-side software and a set of modules for developing client-side applications. .NET components are included for rapid development of client-side software. MegaMatcher 11.0 supports\u003cspan\u003e \u003c\/span\u003e\u003cb\u003eBioAPI 2.0.\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003eTo ensure system compatibility with other software, WSQ component is available, as well as modules for conversion between MegaMatcher template and biometric standards.\u003c\/p\u003e\n\u003cp\u003eMegaMatcher 11.0 is suitable not only for developing\u003cspan\u003e \u003c\/span\u003e\u003cb\u003ecivil AFIS\u003c\/b\u003e, but also for\u003cspan\u003e \u003c\/span\u003e\u003cb\u003eforensic AFIS applications,\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003eas it includes an API for\u003cspan\u003e \u003c\/span\u003e\u003cb\u003elatent fingerprint template editing.\u003c\/b\u003e\u003cspan\u003e \u003c\/span\u003eLatent fingerprint template editing is necessary in order to submit a latent fingerprint (for example, one taken from a crime scene) for the identification into AFIS. Also MegaMatcher is able to\u003cspan\u003e \u003c\/span\u003e\u003cb\u003ematch rolled and flat fingerprints between themselves.\u003c\/b\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003e\u003cspan\u003eThe table below compares MegaMatcher 11.0 Standard SDK and MegaMatcher 11.0 Extnded SDK\u003c\/span\u003e\u003cspan\u003e components.\u003c\/span\u003e\u003c\/b\u003e\u003c\/p\u003e\n\u003cdiv align=\"center\"\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"100%\" class=\"data\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd valign=\"bottom\" width=\"50%\" class=\"cap_left\"\u003eComponent types\u003c\/td\u003e\n\u003ctd width=\"25%\" class=\"cap_top\"\u003eMegaMatcher 11.0\u003cbr\u003eStandard SDK\u003c\/td\u003e\n\u003ctd width=\"25%\" class=\"cap_top\"\u003eMegaMatcher 11.0\u003cbr\u003eExtended SDK\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth colspan=\"3\"\u003eFingerprint component licenses included with a specific SDK:\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Fingerprint Image Processing\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Fast Fingerprint Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Fingerprint Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Fingerprint Extractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Fingerprint Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Fingerprint Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Fingerprint Extractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Fingerprint Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth colspan=\"3\"\u003eFace component licenses included with a specific SDK:\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Face Image Processing\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Fast Face Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Face Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Face Extractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Face Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Face Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Face Extractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Face Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth colspan=\"3\"\u003eIris component licenses included with a specific SDK:\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Iris Image Processing\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Fast Iris Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Iris Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Iris Extractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Iris Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Iris Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Iris Extractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Iris Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth colspan=\"3\"\u003eVoice component licenses included with a specific SDK:\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Voice Processing\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Voice Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Voice Extractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Voice Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Voice Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e3 single computer licenses\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Voice Extractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Mobile Voice Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth colspan=\"3\"\u003ePalm print component licenses included with a specific SDK:\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Palm Print Client\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Palm Print Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth colspan=\"3\"\u003eServer-side matching component licenses included with a specific SDK:\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Matching Server\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• MegaMatcher Accelerator 11.0 Development Edition fingerprint, face and iris engines license\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e\u003cbr\u003e\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003c\/div\u003e\n\u003ch3\u003eMegaMatcher Fingerprint Template Extraction and Matching Engine\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cb\u003eFull MINEX Compliance.\u003c\/b\u003e NIST has recognized MegaMatcher fingerprint algorithm as MINEX compliant and suitable for use in personal identity verification (PIV) program applications.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eRolled and flat fingerprints matching.\u003c\/b\u003e The MegaMatcher fingerprint engine matches rolled and flat fingerprints \u003cb\u003ebetween themselves. \u003c\/b\u003eTypically, conventional \"flat\" fingerprint identification algorithms perform matching between flat and rolled fingerprints less reliably due to the specific deformations of rolled fingerprints. MegaMatcher allows flat-to-flat, flat-to-rolled or rolled-to-rolled fingerprint matching with a high degree of reliability and accuracy. The algorithm matches up to 200,000 flat fingerprint records per second on a single PC.\u003c\/li\u003e\n\u003cli\u003eMegaMatcher includes fingerprint \u003cb\u003eimage quality determination\u003c\/b\u003e, which may be used during enrollment to ensure that only the best quality fingerprint template will be stored in the database.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eTemplate generalization\u003c\/b\u003e is used to generate a better quality template from several fingerprints. Better quality templates result in a higher level of identification accuracy.\u003c\/li\u003e\n\u003cli\u003eMegaMatcher is\u003cb\u003e tolerant to fingerprint translation, rotation and deformation.\u003c\/b\u003e It uses a proprietary fingerprint matching algorithm that identifies fingerprints even if they are rotated, translated or have deformations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eAdaptive image filtration \u003c\/b\u003ealgorithm eliminates noises, ridge ruptures and stuck ridges, and reliably extracting minutiae from even the poorest quality fingerprints in less than 1 second.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eMegaMatcher Face Template Extraction and Matching Engine\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cb\u003eTemplate generalization\u003c\/b\u003e is used to generate a better quality template from several face images. Better quality templates result in a higher level of identification accuracy.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eTolerance to face position\u003c\/b\u003e assures a level of enrollment convenience. MegaMatcher allows for 360 degrees of head roll. Head pitch can be up to 15 degrees in each direction from the frontal position. Head yaw can be up to 45 degrees in each direction from the frontal position. See technical specifications for more details.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eReliable face detection\u003c\/b\u003e assures accurate enrollment from cameras, webcams and various scanned documents; faces may be enrolled from the scanned pages of passports or other types of documentation. When there are \u003cb\u003emultiple faces\u003c\/b\u003e present in a video or an image, they may be enrolled and processed simultaneously. Person's \u003cb\u003egender,\u003c\/b\u003e facial feature points and basic \u003cb\u003eemotions\u003c\/b\u003e can be optionally detected.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eFacial attributes recognition\u003c\/b\u003e. MegaMatcher can be configured to detect certain attributes during the face extraction –\u003cb\u003e smile, open-mouth, closed-eyes, glasses, dark-glasses, beard and moustache.\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eAge estimation.\u003c\/b\u003e MegaMatcher can optionally estimate person's age by analyzing the detected face in the image.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eLive face detection.\u003c\/b\u003e A conventional face identification system can be tricked by placing a photo in front of the camera. MegaMatcher is able to prevent this kind of security breach by determining whether a face in a video stream is \"live\" or a photograph. The liveness detection can be performed in passive mode, when the engine evaluates certain facial features, and in active mode, when the engine evaluates user's response to perform actions like blinking or head movements. See recommendations for live face detection for more details.\u003c\/li\u003e\n\u003cli\u003eThe biometric template record can contain \u003cb\u003eseveral face samples belonging to the same person.\u003c\/b\u003e These samples can be enrolled from different sources and at different times, thus allowing improvement in matching quality. For example, a person might be enrolled with eyeglasses and without, or with different types of eyeglasses; with and without beard or moustache, etc.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eMegaMatcher Voice Template Extraction and Matching Engine\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cb\u003eText-dependent\u003c\/b\u003e voice matching engine determines if a voice sample matches the template that was extracted from a specific phrase. During enrollment, one or more phrases are requested from the person being enrolled. Later that person may be asked to pronounce a specific phrase for verification. This method assures protection against the use of a covertly recorded random phrase from that person.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eTwo-factor authentication with a passphrase\u003c\/b\u003e is performed when a person is asked to say a \u003cb\u003eunique phrase\u003c\/b\u003e (such as passphrase or an answer to a \"secret question\" that is \u003cb\u003eknown only by the person\u003c\/b\u003e being enrolled). The overall system security increases as both voice authenticity and password are checked.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eText-independent \u003c\/b\u003evoice matching engine uses different phrases for user enrollment and recognition. This method is more convenient, as it does not require each user to remember the passphrase. It may be combined with the text-dependent algorithm to perform faster text-independent search with further phrase verification using the more reliable text-dependent algorithm.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eAutomatic voice activity detection.\u003c\/b\u003e The engine is able to detect when users start and finish speaking.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eLiveness detection.\u003c\/b\u003e A system may request each user to enrol a set of unique phrases. Later the user will be requested to say a specific phrase from the enrolled set. This way the system can ensure that a live person is being verified (as opposed to an impostor who uses voice recording).\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eSeveral voice records with the same phrase\u003c\/b\u003e may be stored to improve speaker recognition reliability. Certain natural voice variations (i.e. hoarse voice) or environment changes (i.e. office and outdoors) can be stored in the same template.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eMegaMatcher Iris Template Extraction and Matching Engine\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cb\u003eNIST IREX proven reliability.\u003c\/b\u003e MegaMatcher iris matching engine is based on VeriEye, recognized by NIST as one of the most reliably accurate iris recognition algorithms available.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eFast matching.\u003c\/b\u003e The iris matching speed is up to\u003cb\u003e 200,000 comparisons per second\u003c\/b\u003e on a single PC. See technical specifications for more details.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eRobust iris detection.\u003c\/b\u003e Irises are detected even when there are obstructions to the image, visual noise and\/or different levels of illumination. Lighting reflections, eyelids and eyelashes obstructions are eliminated. Images with narrowed eyelids or eyes that are gazing away are also accepted.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eAutomatic interlacing detection and correction\u003c\/b\u003e results in maximum quality of iris feature templates from moving iris images.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eCorrect iris segmentation\u003c\/b\u003e is obtained even when perfect circles fail, the centres of the iris inner and outer boundaries are different, iris boundaries are definitely not circles and even not ellipses or iris boundaries seem to be perfect circles.\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eIris image quality determination and spoof prevention.\u003c\/b\u003e The image quality estimation can be used during iris enrollment to ensure that only the best quality iris template will be stored into the database. Also, cosmetic (decorative) contact lens, which obscure an iris with some artistic or \u003cb\u003efake iris texture\u003c\/b\u003e and\/or change iris color, can be detected.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003cp\u003eAll biometric templates should be loaded into RAM before identification, thus the maximum biometric templates database size is limited by the amount of available RAM.\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eFingerprint scanners are recommended to have at least \u003cstrong\u003e500 ppi\u003c\/strong\u003e resolution and at least \u003cstrong\u003e1\" x 1\"\u003c\/strong\u003e fingerprint sensors. The specifications are provided for 500 x 500 pixels fingerprint images and templates extracted from these images.\u003c\/li\u003e\n\u003cli\u003eFace capture cameras are recommended to produce at least \u003cstrong\u003e640 x 480 pixels\u003c\/strong\u003e images for reliable faces' detection. Face template extraction and matching speed is not dependent on the image size.\u003c\/li\u003e\n\u003cli\u003eThe \u003cstrong\u003eminimal distance between eyes is 32 pixels\u003c\/strong\u003e for a face on image or video stream to perform face template extraction reliably. \u003cstrong\u003e64 pixels or more recommended\u003c\/strong\u003e for better template extraction results.\u003c\/li\u003e\n\u003cli\u003eFace recognition engine has certain tolerance to face posture:\n\u003cul class=\"complex\"\u003e\n\u003cli\u003ehead \u003cstrong\u003eroll\u003c\/strong\u003e (tilt) – ±180 degrees (configurable); \u003cbr\u003e \u003cstrong\u003e±15 degrees default\u003c\/strong\u003e value is the fastest setting which is usually sufficient for most near-frontal face images.\u003c\/li\u003e\n\u003cli\u003ehead \u003cstrong\u003epitch\u003c\/strong\u003e (nod) – ±15 degrees from frontal position.\u003c\/li\u003e\n\u003cli\u003ehead \u003cstrong\u003eyaw\u003c\/strong\u003e (bobble) – ±45 degrees from frontal position. \u003cbr\u003e \u003cstrong\u003e±15 degrees default\u003c\/strong\u003e value is the fastest setting which is usually sufficient for most near-frontal face images.\u003c\/li\u003e\n\u003c\/ul\u003e\nThe specifications are provided for the default roll and yaw values.\u003c\/li\u003e\n\u003cli\u003eIris capture cameras are recommended to produce at least \u003cstrong\u003e640 x 480 pixels\u003c\/strong\u003e images. The specifications are provided for these images.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eVoice samples of at least 2-seconds in length are recommended\u003c\/strong\u003e to assure speaker recognition quality.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eA minimum 11025 Hz\u003c\/strong\u003e sampling rate, with at least \u003cstrong\u003e16-bit\u003c\/strong\u003e depth, should be used during voice recording.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003eSee also the lists of \u003cstrong\u003ebasic recommendations\u003c\/strong\u003e for facial recognition and speaker recognition.\u003c\/p\u003e\n\u003cp\u003eMegaMatcher biometric template extraction and matching algorithm is designed to run on \u003cstrong\u003emulti-core processors\u003c\/strong\u003e allowing to reach maximum possible performance on the used hardware.\u003c\/p\u003e\n\u003cdiv align=\"center\"\u003e\n\u003ctable style=\"background-color: #ffffff;\" class=\"data\" width=\"100%\" cellspacing=\"0\" cellpadding=\"0\" border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth colspan=\"6\"\u003eMegaMatcher (Current Version) fingerprint engine specifications\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_top\"\u003e\u003cbr\u003e\u003c\/td\u003e\n\u003ctd class=\"cap_top\" colspan=\"2\"\u003e\n\u003cspan style=\"font-size: 90%;\"\u003eEmbedded \/ mobile\u003c\/span\u003e \u003csup\u003e(1)\u003c\/sup\u003e\u003cbr\u003eplatform\u003c\/td\u003e\n\u003ctd class=\"cap_top\" colspan=\"2\"\u003ePC-based \u003csup\u003e(2)\u003c\/sup\u003e\u003cbr\u003eplatform\u003c\/td\u003e\n\u003ctd class=\"cap_top\"\u003eServer\u003cbr\u003eplatform\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" width=\"38%\"\u003eTemplate extraction components\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eEmbedded\u003cbr\u003eFingerprint\u003cbr\u003eExtractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eEmbedded\u003cbr\u003eFingerprint\u003cbr\u003eClient\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eFingerprint\u003cbr\u003eExtractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eFingerprint\u003cbr\u003eClient\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"14%\"\u003eFast\u003cbr\u003eFingerprint\u003cbr\u003eExtractor\u003csup\u003e(3)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTemplate extraction speed\u003cbr\u003e(fingerprints per minute)\u003c\/td\u003e\n\u003ctd\u003e45\u003c\/td\u003e\n\u003ctd\u003e50\u003c\/td\u003e\n\u003ctd\u003e45\u003c\/td\u003e\n\u003ctd\u003e100\u003c\/td\u003e\n\u003ctd\u003e3,000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"border-top: solid 2px #CCC;\"\u003eTemplate matching components\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"2\"\u003eEmbedded\u003cbr\u003eFingerprint\u003cbr\u003eMatcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"2\"\u003eFingerprint\u003cbr\u003eMatcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\"\u003eFast\u003cbr\u003eFingerprint\u003cbr\u003eMatcher\u003csup\u003e(4)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTemplate matching speed\u003cbr\u003e(fingerprints per second)\u003c\/td\u003e\n\u003ctd colspan=\"2\"\u003e3,000\u003c\/td\u003e\n\u003ctd colspan=\"2\"\u003e40,000\u003c\/td\u003e\n\u003ctd\u003e200,000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"border-top: solid 2px #CCC;\"\u003eSingle fingerprint record size in a template \u003csup\u003e(5)\u003c\/sup\u003e (bytes)\u003c\/td\u003e\n\u003ctd style=\"border-top: solid 2px #CCC;\" colspan=\"5\"\u003e700 - 6,000\u003cbr\u003e\u003cspan class=\"smaller\"\u003e(configurable)\u003c\/span\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cbr\u003e\n\u003ctable style=\"background-color: #ffffff;\" class=\"data\" width=\"100%\" cellspacing=\"0\" cellpadding=\"0\" border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth colspan=\"6\"\u003eMegaMatcher (Current Version) face engine specifications\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_top\"\u003e\u003cbr\u003e\u003c\/td\u003e\n\u003ctd class=\"cap_top\" colspan=\"2\"\u003e\n\u003cspan style=\"font-size: 90%;\"\u003eEmbedded \/ mobile\u003c\/span\u003e \u003csup\u003e(1)\u003c\/sup\u003e\u003cbr\u003eplatform\u003c\/td\u003e\n\u003ctd class=\"cap_top\" colspan=\"2\"\u003ePC-based \u003csup\u003e(2)\u003c\/sup\u003e\u003cbr\u003eplatform\u003c\/td\u003e\n\u003ctd class=\"cap_top\"\u003eServer\u003cbr\u003eplatform\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" width=\"38%\"\u003eTemplate extraction components\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eEmbedded\u003cbr\u003eFace\u003cbr\u003eExtractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eEmbedded\u003cbr\u003eFace\u003cbr\u003eClient\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eFace\u003cbr\u003eExtractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eFace\u003cbr\u003eClient\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"14%\"\u003eFast\u003cbr\u003eFace\u003cbr\u003eExtractor\u003csup\u003e(6)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTemplate extraction speed\u003cbr\u003e(faces per minute)\u003c\/td\u003e\n\u003ctd\u003e45\u003c\/td\u003e\n\u003ctd\u003e50\u003c\/td\u003e\n\u003ctd\u003e45\u003c\/td\u003e\n\u003ctd\u003e100\u003c\/td\u003e\n\u003ctd\u003e3,000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"border-top: solid 2px #CCC;\"\u003eTemplate matching components\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"2\"\u003eEmbedded Face Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"2\"\u003eFace Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\"\u003eFast Face Matcher\u003csup\u003e(4)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTemplate matching speed\u003cbr\u003e(faces per second)\u003c\/td\u003e\n\u003ctd colspan=\"2\"\u003e3,000\u003c\/td\u003e\n\u003ctd colspan=\"2\"\u003e40,000\u003c\/td\u003e\n\u003ctd\u003e200,000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"border-top: solid 2px #CCC;\"\u003eSingle face record size in a template \u003csup\u003e(5)\u003c\/sup\u003e (bytes)\u003c\/td\u003e\n\u003ctd style=\"border-top: solid 2px #CCC;\" colspan=\"5\"\u003e4,028 or 5,066 or 7,128\u003cbr\u003e\u003cspan class=\"smaller\"\u003e(configurable)\u003c\/span\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cbr\u003e\n\u003ctable style=\"background-color: #ffffff;\" class=\"data\" width=\"100%\" cellspacing=\"0\" cellpadding=\"0\" border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth colspan=\"6\"\u003eMegaMatcher (Current Version) iris engine specifications\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_top\"\u003e\u003cbr\u003e\u003c\/td\u003e\n\u003ctd class=\"cap_top\" colspan=\"2\"\u003e\n\u003cspan style=\"font-size: 90%;\"\u003eEmbedded \/ mobile\u003c\/span\u003e \u003csup\u003e(1)\u003c\/sup\u003e\u003cbr\u003eplatform\u003c\/td\u003e\n\u003ctd class=\"cap_top\" colspan=\"2\"\u003ePC-based \u003csup\u003e(2)\u003c\/sup\u003e\u003cbr\u003eplatform\u003c\/td\u003e\n\u003ctd class=\"cap_top\"\u003eServer\u003cbr\u003eplatform\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" width=\"38%\"\u003eTemplate extraction components\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eEmbedded\u003cbr\u003eIris\u003cbr\u003eExtractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eEmbedded\u003cbr\u003eIris\u003cbr\u003eClient\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eIris\u003cbr\u003eExtractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eIris\u003cbr\u003eClient\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"14%\"\u003eFast\u003cbr\u003eIris\u003cbr\u003eExtractor\u003csup\u003e(6)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTemplate extraction speed\u003cbr\u003e(irises per minute)\u003c\/td\u003e\n\u003ctd\u003e45\u003c\/td\u003e\n\u003ctd\u003e50\u003c\/td\u003e\n\u003ctd\u003e45\u003c\/td\u003e\n\u003ctd\u003e100\u003c\/td\u003e\n\u003ctd\u003e3,000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"border-top: solid 2px #CCC;\"\u003eTemplate matching components\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"2\"\u003eEmbedded Iris Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"2\"\u003eIris Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\"\u003eFast Iris Matcher\u003csup\u003e(4)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTemplate matching speed\u003cbr\u003e(irises per second)\u003c\/td\u003e\n\u003ctd colspan=\"2\"\u003e3,000\u003c\/td\u003e\n\u003ctd colspan=\"2\"\u003e40,000\u003c\/td\u003e\n\u003ctd\u003e200,000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"border-top: solid 2px #CCC;\"\u003eSingle iris record size in a template \u003csup\u003e(5)\u003c\/sup\u003e (bytes)\u003c\/td\u003e\n\u003ctd style=\"border-top: solid 2px #CCC;\" colspan=\"5\"\u003e2,348\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cbr\u003e\n\u003ctable style=\"background-color: #ffffff;\" class=\"data\" width=\"100%\" cellspacing=\"0\" cellpadding=\"0\" border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth colspan=\"6\"\u003eMegaMatcher (Current Version) voiceprint engine specifications\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_top\"\u003e\u003cbr\u003e\u003c\/td\u003e\n\u003ctd class=\"cap_top\" colspan=\"2\"\u003e\n\u003cspan style=\"font-size: 90%;\"\u003eEmbedded \/ mobile\u003c\/span\u003e \u003csup\u003e(1)\u003c\/sup\u003e\u003cbr\u003eplatform\u003c\/td\u003e\n\u003ctd class=\"cap_top\" colspan=\"2\"\u003ePC-based\u003cbr\u003eplatform\u003c\/td\u003e\n\u003ctd class=\"cap_top\"\u003eServer\u003cbr\u003eplatform\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" width=\"38%\"\u003eTemplate extraction components\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eEmbedded\u003cbr\u003eVoice\u003cbr\u003eExtractor\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eEmbedded\u003cbr\u003eVoice\u003cbr\u003eClient\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eVoice\u003cbr\u003eExtractor\u003csup\u003e(2)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"12%\"\u003eVoice\u003cbr\u003eClient\u003csup\u003e(2)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%;\" width=\"14%\"\u003eFast\u003cbr\u003eVoice\u003cbr\u003eExtractor\u003csup\u003e(6)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTemplate extraction speed\u003cbr\u003e(voiceprints per minute)\u003c\/td\u003e\n\u003ctd\u003e45\u003c\/td\u003e\n\u003ctd\u003e50\u003c\/td\u003e\n\u003ctd\u003e45\u003c\/td\u003e\n\u003ctd\u003e100\u003c\/td\u003e\n\u003ctd\u003e3,000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"border-top: solid 2px #CCC;\"\u003eTemplate matching components\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"2\"\u003eEmbedded Voice Matcher\u003c\/td\u003e\n\u003ctd style=\"font-size: 80%; border-top: solid 2px #CCC;\" colspan=\"3\"\u003eVoice Matcher\u003csup\u003e(4)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTemplate matching speed\u003cbr\u003e(voiceprints per second)\u003c\/td\u003e\n\u003ctd colspan=\"2\"\u003e100\u003c\/td\u003e\n\u003ctd colspan=\"3\"\u003e8,000\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" style=\"border-top: solid 2px #CCC;\"\u003eSingle voiceprint record size in a template \u003csup\u003e(5)\u003c\/sup\u003e \u003csup\u003e(7)\u003c\/sup\u003e (bytes)\u003c\/td\u003e\n\u003ctd style=\"border-top: solid 2px #CCC;\" colspan=\"5\"\u003e3,500 - 4,500\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003c\/div\u003e\n\u003cp style=\"font-size: 90%;\"\u003eNotes: \u003cbr\u003e (1) Requires to be run on \u003cstrong\u003eiOS\u003c\/strong\u003e devices or \u003cstrong\u003eAndroid\u003c\/strong\u003e devices based on at least \u003cstrong\u003eSnapdragon S4\u003c\/strong\u003e system-on-chip with \u003cstrong\u003eKrait 300\u003c\/strong\u003e processor (4 cores, 1.51 GHz). \u003cbr\u003e (2) Requires to be run on \u003cstrong\u003ePC or laptop\u003c\/strong\u003e with at least Intel \u003cstrong\u003eCore 2 Q9400\u003c\/strong\u003e quad-core processor (2.67 GHz) to reach the specified performance. \u003cbr\u003e (3) Requires to be run on server hardware with at least \u003cstrong\u003eDual Intel Xeon processors E5-2680V2 (2.8 GHz)\u003c\/strong\u003e to reach the specified performance. \u003cbr\u003e (4) Requires to be run on PC with at least Intel \u003cstrong\u003eCore i7-4771\u003c\/strong\u003e quad-core processor (\u003cstrong\u003e3.5 GHz\u003c\/strong\u003e) to reach the specified performance. \u003cbr\u003e (5) MegaMatcher (Current Version) allows to store multiple biometric records of the same or different biometric modalities in a template; in this case the template size is the sum of all included biometric records. \u003cbr\u003e (6) Requires to be run on server hardware with at least \u003cstrong\u003eIntel Xeon E5-2680V2 processor (2.8 GHz)\u003c\/strong\u003e to reach the specified performance. \u003cbr\u003e (7) The specifications are provided for \u003cstrong\u003e5-second long voice samples\u003c\/strong\u003e; template size has linear dependence from voice sample length.\u003c\/p\u003e\n\u003cp\u003eSee also: technical specifications for MegaMatcher Palm Print engine.\u003c\/p\u003e\n\u003cp\u003eNever publish dirty markup and double-check your content before publishing a web article!\u003c\/p\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":41331019579494,"sku":"100500","price":2487.37,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/megamatcher-sdk.jpg?v=1714422358"},{"product_id":"megamatcher-abis-starting-kit","title":"MegaMatcher ABIS Starting Kit","description":"\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher ABIS 11.0 Starting Kit includes the following components:\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eManagement Service – 1 single computer license;\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eImage Processing Service – 1 single computer license;\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eManagement Service Development Edition – 1 single computer license;\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher ABIS Client Application – 10 single computer licenses.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cspan data-mce-fragment=\"1\"\u003eThe required additional components installation licenses and\/or customization for specific project needs can be ordered at any time.\u003c\/span\u003e\n\u003cp data-mce-fragment=\"1\"\u003e \u003cbr data-mce-fragment=\"1\"\u003e\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher Automated Biometric Identification System is a complete system for the deployment of large-scale multi-biometric projects. The modular and customizable solution provides services for high-performance, scalable systems with multiple parallel transactions.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eThe solution is intended for national-scale projects, like biometric voter registration with records deduplication, passport issuing, border control, as well as other civil or criminal AFIS\/ABIS.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eAvailable as on-premise solution and as a cloud service.\u003c\/p\u003e\n\u003ch3 data-mce-fragment=\"1\"\u003eFeatures and Capabilities\u003c\/h3\u003e\n\u003cp data-mce-fragment=\"1\"\u003e \u003cbr data-mce-fragment=\"1\"\u003e\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMultiple complex biometric transaction processing with high speed and accuracy.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eTechnology proven in national-scale projects, like passport issuance and voter deduplication.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eFingerprint, face and iris modalities supported.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eNIST MINEX-compliant fingerprint engine, NIST IREX proven iris engine.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eScalable, modular architecture with possible customization for project needs.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eCloud service available for making the system accessible from multiple platforms and locations.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eHigh availability and fault tolerance.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eInteroperability with other systems.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eSupport for ANSI and ISO biometric template standards, ICAO requirements.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp data-mce-fragment=\"1\"\u003e \u003cbr data-mce-fragment=\"1\"\u003e\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher ABIS 11.0 on-premise solution is designed as a complete system with all necessary components for deploying a large-scale biometric system. The solution includes ready-to-use services and applications for running on regular hardware.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher ABIS 11.0 on-premise solution provides these capabilities for large-scale biometric identification systems:\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003e\n\u003cb data-mce-fragment=\"1\"\u003eHigh performance.\u003c\/b\u003e\u003cspan data-mce-fragment=\"1\"\u003e \u003c\/span\u003eMegaMatcher Automated Biometric Identification System is designed for fast processing of multiple biometric transactions with high accuracy and reliability. The Management Service distributes external requests between the corresponding services. The Image Processing Service performs parallel biometric template extraction from multiple images. The Matching Service can store biometric and demographic information for unlimited number of persons as well as perform fast searches in the whole database.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003e\n\u003cb data-mce-fragment=\"1\"\u003eFingerprint, face and iris modalities support.\u003c\/b\u003e\u003cspan data-mce-fragment=\"1\"\u003e \u003c\/span\u003eThe system can accept fingerprint, face and iris images for creating biometric templates and searching against the database. Each template can contain multiple fingerprints, irises or faces. Proprietary fused matching algorithm provides high matching accuracy. .\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003e\n\u003cb data-mce-fragment=\"1\"\u003eBiometric adjudication.\u003c\/b\u003e\u003cspan data-mce-fragment=\"1\"\u003e \u003c\/span\u003eMegaMatcher ABIS can determine questionable biometric matching results like suspicious duplicate(s) or non-matching templates and forward them to human experts for manual adjudication. A specialized visual tool is provided to human experts to facilitate decision making.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003e\n\u003cb data-mce-fragment=\"1\"\u003eInteroperability with other systems.\u003c\/b\u003e\u003cspan data-mce-fragment=\"1\"\u003e \u003c\/span\u003eWeb-services are provided for communication with third party biometric systems to ensure all aspects of required biometric services as biometric data storing, update, identification, verification and submission of matching results.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003e\n\u003cb data-mce-fragment=\"1\"\u003eHigh availability and fault tolerance.\u003c\/b\u003e\u003cspan data-mce-fragment=\"1\"\u003e \u003c\/span\u003eMegaMatcher ABIS architecture allows to reach high system reliability and better performance by running instances of some or all components in parallel. If an instance of a component becomes unavailable, the other instances of the component can still accept incoming requests and perform corresponding operations. All communications are designed as atomic transactions, thus in case of failure no information is lost or corrupted.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003e\n\u003cb data-mce-fragment=\"1\"\u003eCustomization for project needs.\u003c\/b\u003e\u003cspan data-mce-fragment=\"1\"\u003e \u003c\/span\u003eMost components of MegaMatcher ABIS can be customized for specific project needs and restrictions. The customization may range from user interface translation into required language to modifying the system architecture.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003e\n\u003cb data-mce-fragment=\"1\"\u003eAccuracy.\u003c\/b\u003e\u003cspan data-mce-fragment=\"1\"\u003e \u003c\/span\u003eMegaMatcher ABIS is based on award-winning biometric technologies. In 2018 NIST has judged that Neurotechnology's fingerprint algorithms are the most accurate high-speed fingerprint recognition systems among all MINEX III participants. In the same year, the iris recognition algorithm have been proven by NIST as the second most accurate, and the accelerated version of the algorithm provided the fastest matching than any other matcher in the IREX IX evaluation.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003e\n\u003cb data-mce-fragment=\"1\"\u003eBiometric standards support.\u003c\/b\u003e\u003cspan data-mce-fragment=\"1\"\u003e \u003c\/span\u003eMegaMatcher ABIS 11.0 allows the use of ANSI\/NIST-ITL-1, ISO\/IEC 19794-2, ISO\/IEC 19794-5 and ISO\/IEC 19794-6 biometric template standards. Face images checking for compliance with ICAO requirements is also available.\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":41331020005478,"sku":"100540","price":12888.33,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo200523-2-min_5b5a7a97-7445-44cb-9d5f-6beb226decf2.jpg?v=1714422360"},{"product_id":"megamatcher-accelerator-standard-face","title":"MegaMatcher Accelerator - Standard - Face","description":"\u003cp\u003e\u003cspan data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Standard Face Edition is a ready-to-use software products for fast iris and face matching on the server-sie of an AFIS or multi-biometric system. This product is intended for large-scale biometric projects with up to several million people enrolled in the database.\u003c\/span\u003e\u003cbr data-mce-fragment=\"1\"\u003e\u003cbr data-mce-fragment=\"1\"\u003e\u003cspan data-mce-fragment=\"1\"\u003eT\u003c\/span\u003e\u003cspan data-mce-fragment=\"1\"\u003ehe \u003c\/span\u003e\u003cstrong data-mce-fragment=\"1\"\u003eExtended\u003c\/strong\u003e\u003cspan data-mce-fragment=\"1\"\u003e versions of this product \u003c\/span\u003e\u003cstrong data-mce-fragment=\"1\"\u003einclude server hardware\u003c\/strong\u003e\u003cspan data-mce-fragment=\"1\"\u003e and software for fast biometric template matching on server-side part of a large-scale AFIS or multi-modal system. The \u003c\/span\u003e\u003cstrong data-mce-fragment=\"1\"\u003eStandard\u003c\/strong\u003e\u003cspan data-mce-fragment=\"1\"\u003e version is intended to be run on a \u003c\/span\u003e\u003cstrong data-mce-fragment=\"1\"\u003ecommon PC\/Server\u003c\/strong\u003e\u003cspan data-mce-fragment=\"1\"\u003e and does not include any hardware.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e \u003c\/p\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":41331020038246,"sku":"100552","price":17196.37,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo_262409c1-bec7-4073-a4db-cf0b00ad74fc.jpg?v=1714422362"},{"product_id":"megamatcher-accelerator-standard-palm","title":"MegaMatcher Accelerator - Standard - Palm","description":"\u003cp data-mce-fragment=\"1\"\u003eThe palm print matching engine can be used separately or with the other fingerprint, iris, and face matching engines. The palm print matching engine is part of the MegaMatcher Accelerator 11.1 Standard family of ready-to-use software products for fast fingerprint, palm print, iris and face matching on the server-side of an AFIS or multi-biometric system. These products are intended for large-scale biometric projects with up to several million people enrolled in the database.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eEach license allows the use of the included engines on a single server unit.\u003c\/p\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":41331020103782,"sku":"100555","price":25790.9,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo200523-2-min_de89c9d3-3a06-4311-89a9-40f473e188cf.jpg?v=1714422364"},{"product_id":"megamatcher-accelerator-extreme-finger","title":"MegaMatcher Accelerator - Extreme - Finger","description":"\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator is a ready-to-use server-side solution that accepts tasks from client-side software. Integrators develop client-side software according to their needs and then deploy the system as a whole.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme software licenses are available for new and existing customers of MegaMatcher Extended SDK.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme is designed to run on server hardware with dual Xeon processors, GPU and 512 GB of RAM. This version is shipped as an installation CD image that includes Linux OS and fast multi-biometric identification software. Optionally, a ready-to-use solution with server hardware and pre-installed MegaMatcher Accelerator software can be provided.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 is available in these versions:\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 fingerprint engine license.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 iris engine license.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 face engine license.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 fingerprint and face engines license – the engines may be used as a fused matching engine.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 fingerprint and iris engines license – the engines may be used as a fused matching engine.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 face and iris engines license – the engines may be used as a fused matching engine.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 fingerprint, face and iris engines license – the engines may be used as a fused matching engine.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eFeatures and Capabilities\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003eProven in national-scale projects, including voter registration and national ID.\u003c\/li\u003e\n\u003cli\u003eAvailable as a ready-to-use biometric solution with server hardware or as biometric software that will run on server hardware or a common PC.\u003c\/li\u003e\n\u003cli\u003eUp to 1,200,000,000 fingerprints or 1,200,000,000 faces or 700,000,000 irises per second matching speed on a single unit.\u003c\/li\u003e\n\u003cli\u003eFingerprint, iris, face and voice modalities supported.\u003c\/li\u003e\n\u003cli\u003eScalable cluster architecture.\u003c\/li\u003e\n\u003cli\u003eSupport for ISO \u0026amp; ANSI fingerprint template standards.\u003c\/li\u003e\n\u003cli\u003eSuitable for duplicates search.\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":41331020136550,"sku":"100562","price":167743.7,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo_c3ddc7e0-2eb5-4df0-b901-f80099c5880c.jpg?v=1714422366"},{"product_id":"megamatcher-accelerator-extreme-iris","title":"MegaMatcher Accelerator - Extreme - Iris","description":"\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator is a ready-to-use server-side solution that accepts tasks from client-side software. Integrators develop client-side software according to their needs and then deploy the system as a whole.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme software licenses are available for new and existing customers of MegaMatcher Extended SDK.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme is designed to run on server hardware with dual Xeon processors, GPU and 512 GB of RAM. This version is shipped as an installation CD image that includes Linux OS and fast multi-biometric identification software. Optionally, a ready-to-use solution with server hardware and pre-installed MegaMatcher Accelerator software can be provided.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 is available in these versions:\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 fingerprint engine license.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 iris engine license.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 face engine license.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 fingerprint and face engines license – the engines may be used as a fused matching engine.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 fingerprint and iris engines license – the engines may be used as a fused matching engine.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 face and iris engines license – the engines may be used as a fused matching engine.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 fingerprint, face and iris engines license – the engines may be used as a fused matching engine.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eFeatures and Capabilities\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003eProven in national-scale projects, including voter registration and national ID.\u003c\/li\u003e\n\u003cli\u003eAvailable as a ready-to-use biometric solution with server hardware or as biometric software that will run on server hardware or a common PC.\u003c\/li\u003e\n\u003cli\u003eUp to 1,200,000,000 fingerprints or 1,200,000,000 faces or 700,000,000 irises per second matching speed on a single unit.\u003c\/li\u003e\n\u003cli\u003eFingerprint, iris, face and voice modalities supported.\u003c\/li\u003e\n\u003cli\u003eScalable cluster architecture.\u003c\/li\u003e\n\u003cli\u003eSupport for ISO \u0026amp; ANSI fingerprint template standards.\u003c\/li\u003e\n\u003cli\u003eSuitable for duplicates search.\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":41331020333158,"sku":"100565","price":167743.7,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo200523-2-min_aa18080f-b854-4d85-abf6-7b71ffbb8a96.jpg?v=1714422369"},{"product_id":"megamatcher-accelerator-extreme-face","title":"MegaMatcher Accelerator - Extreme - Face","description":"\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator is a ready-to-use server-side solution that accepts tasks from client-side software. Integrators develop client-side software according to their needs and then deploy the system as a whole.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme software licenses are available for new and existing customers of MegaMatcher Extended SDK.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme is designed to run on server hardware with dual Xeon processors, GPU and 512 GB of RAM. This version is shipped as an installation CD image that includes Linux OS and fast multi-biometric identification software. Optionally, a ready-to-use solution with server hardware and pre-installed MegaMatcher Accelerator software can be provided.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 is available in these versions:\u003c\/p\u003e\n\u003cul data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 fingerprint engine license.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 iris engine license.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 face engine license.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 fingerprint and face engines license – the engines may be used as a fused matching engine.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 fingerprint and iris engines license – the engines may be used as a fused matching engine.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 face and iris engines license – the engines may be used as a fused matching engine.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator Extreme 10.0 fingerprint, face and iris engines license – the engines may be used as a fused matching engine.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eFeatures and Capabilities\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003eProven in national-scale projects, including voter registration and national ID.\u003c\/li\u003e\n\u003cli\u003eAvailable as a ready-to-use biometric solution with server hardware or as biometric software that will run on server hardware or a common PC.\u003c\/li\u003e\n\u003cli\u003eUp to 1,200,000,000 fingerprints or 1,200,000,000 faces or 700,000,000 irises per second matching speed on a single unit.\u003c\/li\u003e\n\u003cli\u003eFingerprint, iris, face and voice modalities supported.\u003c\/li\u003e\n\u003cli\u003eScalable cluster architecture.\u003c\/li\u003e\n\u003cli\u003eSupport for ISO \u0026amp; ANSI fingerprint template standards.\u003c\/li\u003e\n\u003cli\u003eSuitable for duplicates search.\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":41331020365926,"sku":"100566","price":167743.7,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo_69cd75c5-237e-499d-a49c-1708a10569a5.jpg?v=1714422371"},{"product_id":"megamatcher-accelerator-extended-palm","title":"MegaMatcher Accelerator - Extended - Palm","description":"\u003cp data-mce-fragment=\"1\"\u003eThe palm print matching engine can be used separately or with the other fingerprint, iris, and face matching engines. The palm print matching engine is part of the MegaMatcher Accelerator 11.1 Extended family of ready-to-use software products for fast fingerprint, palm print, iris and face matching on the server-side of an AFIS or multi-biometric system. The solutions are intended for national-scale biometric identification projects with millions of people enrolled in the database.\u003c\/p\u003e\n\u003cspan data-mce-fragment=\"1\"\u003eEach license allows the use of the included engines on a single server unit.\u003c\/span\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":41331020562534,"sku":"100567","price":65784.03,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo_28050a67-ec34-4e57-beff-1e2a77c7d29f.jpg?v=1714422373"},{"product_id":"megamatcher-accelerator-extended-iris","title":"MegaMatcher Accelerator - Extended - Iris","description":"\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher Extended Accelerator 3.0 is a solution for fast template matching on the server-side part of a large-scale AFIS or multi-biometric system. The\u003cspan data-mce-fragment=\"1\"\u003e \u003c\/span\u003e\u003cstrong data-mce-fragment=\"1\"\u003eExtended\u003c\/strong\u003e\u003cspan data-mce-fragment=\"1\"\u003e \u003c\/span\u003eversion includes software for fast biometric template matching on the server-side part of a large-scale AFIS or multi-modal system.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eMegaMatcher Accelerator 3.0 Extended units and MegaMatcher Accelerator 3.0 Standard software can be purchased by new and existing MegaMatcher SDK, VeriFinger SDK and VeriEye SDK customers.\u003c\/p\u003e\n\u003ch2 data-mce-fragment=\"1\"\u003eAdvantages of MegaMatcher\u003c\/h2\u003e\n\u003cul class=\"complex\" data-mce-fragment=\"1\"\u003e\n\u003cli data-mce-fragment=\"1\"\u003eAvailable as ready-to-use biometric solution with server hardware\u003cbr data-mce-fragment=\"1\"\u003eor as biometric software for running on a common PC.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eUp to 200,000,000 irises or 100,000,000 fingerprints per second matching speed on a single unit.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eFingerprint, iris and face modalities supported.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eScalable cluster architecture.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eISO \u0026amp; ANSI fingerprint template standards support.\u003c\/li\u003e\n\u003cli data-mce-fragment=\"1\"\u003eSuitable for duplicates search.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eMegaMatcher Accelerator features and capabilities\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMegaMatcher Accelerator Extended\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eis\u003cspan\u003e \u003c\/span\u003e\u003cstrong\u003eready-to-use software solution\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003efor fast multi-biometric identification software. The solution does not require any additional development and accepts requests from client software via network or Web.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFast matching.\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eA single MegaMatcher Accelerator Extended unit can match up to\u003cspan\u003e \u003c\/span\u003e\u003cstrong\u003e100 million fingerprints\u003cspan\u003e \u003c\/span\u003e\u003c\/strong\u003eper second or up to\u003cspan\u003e \u003c\/span\u003e\u003cstrong\u003e200 million irises\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eper second in 1-to-many mode using Neurotechnology proprietary biometric template format.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMultiple modalities support.\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eMegaMatcher Accelerator can be used within a biometric system that contains templates with any number of fingerprint, iris and\/or face records.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFull database search.\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eThe biometric engines included in MegaMatcher Accelerator do not perform internal database indexing or pre-classification (by fingerprint type, eye color etc) thus avoiding false rejections when incorrect classificators appear. This way the whole database is scanned comprehensively during every matching request and very low false rejection ensured. On the other hand, integrators may use non-biometric classificators like gender or country's region to optimize system size.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eOptimal system size.\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eA system based on MegaMatcher Accelerator solution can be configured to perform fast candidates selection using irises and\/or several fingerprints, and then use other biometric modalities to validate selection results. This approach allows to reach optimal matching speed and reliability while keeping the overall system cost within the defined limits.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eISO \u0026amp; ANSI standards support.\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eMegaMatcher Accelerator allows to use ANSI and ISO biometric standards for fingerprint templates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eScalable architecture.\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eMultiple MegaMatcher Accelerator units can be combined together in a\u003cspan\u003e \u003c\/span\u003e\u003cstrong\u003ecluster\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003efor higher matching speed. For example, a cluster of 5 MegaMatcher Accelerator Extended units would allow to match about 145 million templates per second (when a template contains 4 fingerprint records), a cluster of 10 units – about 290 million templates per second, and so on. No additional cluster software is required, as MegaMatcher Accelerator includes all necessary software. The customers only need to assign one MegaMatcher Accelerator unit as a primary unit in a cluster.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSuitable for duplicates search.\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eSearching for duplicates in a biometric templates database is a task that requires many computations, as each biometric template needs to be verified with each other template in the database. MegaMatcher Accelerator provides enough productivity to complete duplicate searching in a reasonable time. Scalable architecture allows the combination of several MegaMatcher Accelerator units for tasks involving bigger databases.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003ch2\u003eMegaMatcher Accelerator features and capabilities\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMegaMatcher Accelerator Extended\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eis\u003cspan\u003e \u003c\/span\u003e\u003cstrong\u003eready-to-use software solution\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003efor fast multi-biometric identification software. The solution does not require any additional development and accepts requests from client software via network or Web.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFast matching.\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eA single MegaMatcher Accelerator Extended unit can match up to\u003cspan\u003e \u003c\/span\u003e\u003cstrong\u003e100 million fingerprints\u003cspan\u003e \u003c\/span\u003e\u003c\/strong\u003eper second or up to\u003cspan\u003e \u003c\/span\u003e\u003cstrong\u003e200 million irises\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eper second in 1-to-many mode using Neurotechnology proprietary biometric template format.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMultiple modalities support.\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eMegaMatcher Accelerator can be used within a biometric system that contains templates with any number of fingerprint, iris and\/or face records.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFull database search.\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eThe biometric engines included in MegaMatcher Accelerator do not perform internal database indexing or pre-classification (by fingerprint type, eye color etc) thus avoiding false rejections when incorrect classificators appear. This way the whole database is scanned comprehensively during every matching request and very low false rejection ensured. On the other hand, integrators may use non-biometric classificators like gender or country's region to optimize system size.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eOptimal system size.\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eA system based on MegaMatcher Accelerator solution can be configured to perform fast candidates selection using irises and\/or several fingerprints, and then use other biometric modalities to validate selection results. This approach allows to reach optimal matching speed and reliability while keeping the overall system cost within the defined limits.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eISO \u0026amp; ANSI standards support.\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eMegaMatcher Accelerator allows to use ANSI and ISO biometric standards for fingerprint templates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eScalable architecture.\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eMultiple MegaMatcher Accelerator units can be combined together in a\u003cspan\u003e \u003c\/span\u003e\u003cstrong\u003ecluster\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003efor higher matching speed. For example, a cluster of 5 MegaMatcher Accelerator Extended units would allow to match about 145 million templates per second (when a template contains 4 fingerprint records), a cluster of 10 units – about 290 million templates per second, and so on. No additional cluster software is required, as MegaMatcher Accelerator includes all necessary software. The customers only need to assign one MegaMatcher Accelerator unit as a primary unit in a cluster.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSuitable for duplicates search.\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eSearching for duplicates in a biometric templates database is a task that requires many computations, as each biometric template needs to be verified with each other template in the database. MegaMatcher Accelerator provides enough productivity to complete duplicate searching in a reasonable time. Scalable architecture allows the combination of several MegaMatcher Accelerator units for tasks involving bigger databases.\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":41331020628070,"sku":"100568","price":43856.74,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/prt_neuro.jpg?v=1714422375"},{"product_id":"megamatcher-accelerator-development-edition-finger","title":"MegaMatcher Accelerator - Development Edition - Finger","description":"\u003cp\u003e\u003cspan data-mce-fragment=\"1\"\u003eThe MegaMatcher Development Edition - Finger - software is intended for developers who need to run MegaMatcher Accelerator software in-house for software development and support without the need to purchase a dedicated Standard or Extended unit. It is also suitable for deploying pilot projects as well as biometric projects with up to several million people enrolled in the database.\u003c\/span\u003e\u003cbr data-mce-fragment=\"1\"\u003e\u003c\/p\u003e\n\u003ch2\u003eMegaMatcher Accelerator Development Features\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eProvides the same API for developers as the Standard and Extended Accelerators, thus the system deployment only requires to replace it with MegaMatcher Accelerator Standard or Extended.\u003c\/li\u003e\n\u003cli\u003eHas the same database capacity as the MegaMatcher Accelerator Standard, but lower matching speed.\u003c\/li\u003e\n\u003cli\u003eFast fingerprint, iris and face matching engines can be used separately or together.\u003c\/li\u003e\n\u003cli\u003eHardware is not included\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":41331020660838,"sku":"100580","price":2580.28,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo_f9ac9687-67d2-44e6-84d4-2b75f58db7c7.jpg?v=1714422378"},{"product_id":"megamatcher-accelerator-development-edition-iris","title":"MegaMatcher Accelerator - Development Edition - Iris","description":"\u003cp\u003e\u003cspan data-mce-fragment=\"1\"\u003eThe MegaMatcher Development Accelerator Iris Edition software is intended for developers who need to run MegaMatcher Accelerator software in-house for software development and support without the need to purchase a dedicated Standard or Extended unit. It is also suitable for deploying pilot projects as well as biometric projects with up to several million people enrolled in the database.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch2\u003eMegaMatcher Accelerator Development Features\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eProvides the same API for developers as the Standard and Extended Accelerators, thus the system deployment only requires to replace it with MegaMatcher Accelerator Standard or Extended.\u003c\/li\u003e\n\u003cli\u003eHas the same database capacity as the MegaMatcher Accelerator Standard, but lower matching speed.\u003c\/li\u003e\n\u003cli\u003eFast fingerprint, iris and face matching engines can be used separately or together.\u003c\/li\u003e\n\u003cli\u003eHardware is not included\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":41331020857446,"sku":"100582","price":2580.28,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo_75c9b596-1af1-4f18-a376-5ad39da5413b.jpg?v=1714422380"},{"product_id":"megamatcher-accelerator-development-edition-face","title":"MegaMatcher Accelerator - Development Edition - Face","description":"\u003cp\u003e\u003cspan data-mce-fragment=\"1\"\u003eThe MegaMatcher Accelerator Development Edition - Face - software is intended for developers who need to run MegaMatcher Accelerator software in-house for software development and support without the need to purchase a dedicated Standard or Extended unit. It is also suitable for deploying pilot projects as well as biometric projects with up to several million people enrolled in the database.\u003c\/span\u003e\u003c\/p\u003e\n\u003ch2\u003eMegaMatcher Accelerator Development Features\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eProvides the same API for developers as the Standard and Extended Accelerators, thus the system deployment only requires to replace it with MegaMatcher Accelerator 7.2 Standard or Extended.\u003c\/li\u003e\n\u003cli\u003eHas the same database capacity as the MegaMatcher Accelerator 7.2 Standard, but lower matching speed.\u003c\/li\u003e\n\u003cli\u003eFast fingerprint, iris and face matching engines can be used separately or together.\u003c\/li\u003e\n\u003cli\u003eHardware is not included\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e \u003c\/p\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":41331020890214,"sku":"100584","price":2580.28,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo_a775cde8-d07e-400f-9f3d-cc791140343e.jpg?v=1714422382"},{"product_id":"megamatcher-accelerator-development-edition-palm","title":"MegaMatcher Accelerator - Development Edition - Palm","description":"\u003cp data-mce-fragment=\"1\"\u003eThe palm print matching engine can be used separately or with the other fingerprint, iris, and face matching engines. The palm print matching engine is part of the MegaMatcher Accelerator 11.1 Development Edition software which is intended for developers who need to run MegaMatcher Accelerator software in-house for software development and support without the need to purchase a dedicated Standard or Extended unit. It is also suitable for deploying pilot projects, as well as biometric projects with up to several million people enrolled in the database.\u003c\/p\u003e\n\u003cp data-mce-fragment=\"1\"\u003eEach license allows the use of the included engines on a single server unit.\u003c\/p\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":41331021054054,"sku":"100585","price":3870.13,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/neurotlogo200523-2-min_73d46792-9ce3-4dfa-87a7-d41ef176ff93.jpg?v=1714422384"},{"product_id":"megamatcher-on-card-sdk","title":"MegaMatcher on Card SDK","description":"\u003ch2 data-mce-fragment=\"1\" class=\"title_front\"\u003eSmart card multi-biometrics\u003c\/h2\u003e\n\u003cp\u003eMegaMatcher On Card SDK offers matching-on-card technology that stores a person's fingerprint, iris and face templates on a smart card and performs template matching in a microprocessor embedded in the card, instead of matching biometric information on a PC processor. \u003cbr\u003e The match-on-card method ensures that personal biometric information does not transfer to an external computer as it would in a more basic template-on-card system.\u003c\/p\u003e\n\u003cul class=\"complex\"\u003e\n\u003cli\u003eNIST MINEX-compliant fingerprint engine\u003c\/li\u003e\n\u003cli\u003ePC-like verification accuracy\u003c\/li\u003e\n\u003cli\u003eConfigurable verification modes\u003c\/li\u003e\n\u003cli\u003eSecurity and privacy\u003c\/li\u003e\n\u003cli\u003eMulti-biometrics support\u003c\/li\u003e\n\u003cli\u003eISO\/IEC standards support\u003c\/li\u003e\n\u003cli\u003eEasy integration with existing systems\u003c\/li\u003e\n\u003cli\u003eDifferent smart card platforms supported\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eSDK Contents\u003c\/h2\u003e\n\u003cp class=\"list_cap\"\u003eThe table below lists the components of MegaMatcher On Card 11.0 SDK:\u003c\/p\u003e\n\u003cdiv style=\"margin: 1em 0em;\" align=\"center\"\u003e\n\u003ctable class=\"data\" width=\"100%\" cellspacing=\"0\" cellpadding=\"0\" border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\" width=\"40%\" valign=\"bottom\"\u003eComponents\u003c\/td\u003e\n\u003ctd class=\"cap_top\" width=\"15%\"\u003eMicrosoft Windows \u003cbr\u003e\u003cspan style=\"font-size: 80%;\"\u003e(32 \u0026amp; 64 bit)\u003c\/span\u003e\n\u003c\/td\u003e\n\u003ctd class=\"cap_top\" width=\"15%\"\u003eLinux \u003cbr\u003e\u003cspan style=\"font-size: 80%;\"\u003e(32 \u0026amp; 64 bit)\u003c\/span\u003e\n\u003c\/td\u003e\n\u003ctd class=\"cap_top\" width=\"15%\"\u003eMac OS X \u003cbr\u003e\u003cspan style=\"font-size: 80%;\"\u003e(32 \u0026amp; 64 bit)\u003c\/span\u003e\n\u003c\/td\u003e\n\u003ctd class=\"cap_top\" width=\"15%\"\u003eAndroid \u003cbr\u003e\u003cspan style=\"font-size: 80%;\"\u003e(32 \u0026amp; 64 bit)\u003c\/span\u003e\n\u003c\/td\u003e\n\u003ctd class=\"cap_top\" width=\"15%\"\u003eJavaCard OS\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Smart card with fingerprint matching engine\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e2 smart cards\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Smart card with multi-modal fingerprint, face and iris matching engine\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd style=\"font-size: 90%;\"\u003e1 smart card\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Fingerprint Card Extractor\u003c\/td\u003e\n\u003ctd colspan=\"4\" style=\"font-size: 90%;\"\u003e2 single computer licenses\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Face Card Extractor\u003c\/td\u003e\n\u003ctd colspan=\"4\" style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Iris Card Extractor\u003c\/td\u003e\n\u003ctd colspan=\"4\" style=\"font-size: 90%;\"\u003e1 single computer license\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Library for communication with a smart card\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Device manager library\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth colspan=\"6\"\u003eProgramming samples\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• C#\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Visual Basic .NET\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Java\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• JavaCard (enrollment and verification applets)\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth colspan=\"6\"\u003eProgramming tutorials\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• C\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• C++\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• C#\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Visual Basic .NET\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• Java\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• JCDKv2.2.2 apdutool\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• NXP JCOP tools JCShell\u003c\/td\u003e\n\u003ctd\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003ctd\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003cth colspan=\"6\"\u003eDocumentation\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003e• MegaMatcher On Card SDK documentation\u003c\/td\u003e\n\u003ctd colspan=\"5\"\u003e\u003cstrong\u003e+\u003c\/strong\u003e\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003c\/div\u003e\n\u003ch2\u003eMegaMatcher On Card fingerprint matching engine\u003c\/h2\u003e\n\u003cp\u003eMegaMatcher On Card 11.0 fingerprint matching engine performs fingerprint template matching in 1-to-1 mode (verification). Being based on the MegaMatcher technology, the engine is tolerant to fingerprint rotations, translations and deformations.\u003c\/p\u003e\n\u003ch2\u003eMegaMatcher On Card face matching engine\u003c\/h2\u003e\n\u003cp\u003eMegaMatcher On Card 11.0 face matching engine performs face template matching in 1-to-1 mode (verification).\u003c\/p\u003e\n\u003ch2\u003eMegaMatcher On Card iris matching engine\u003c\/h2\u003e\n\u003cp\u003eMegaMatcher On Card 11.0 iris matching engine performs iris template matching in 1-to-1 mode (verification).\u003c\/p\u003e\n\u003ch2\u003eFingerprint Card Extractor component\u003c\/h2\u003e\n\u003cp\u003eFingerprint Card Extractor creates ISO\/IEC 19794-2 on-card comparison format fingerprint templates from fingerprint images.\u003c\/p\u003e\n\u003ch2\u003eFace Card Extractor component\u003c\/h2\u003e\n\u003cp\u003eFace Card Extractor creates face templates in proprietary on-card comparison format from face images. The Extractor can generalize a face template from several face images to improve the template's quality. The algorithm has also the ability to recognize whether a face in a video stream belongs to a real human or is a photo, in order to improve the overall security of the system.\u003c\/p\u003e\n\u003ch2\u003eIris Card Extractor component\u003c\/h2\u003e\n\u003cp\u003eIris Card Extractor creates iris templates in proprietary on-card comparison format from eye images.\u003c\/p\u003e\n\u003ch2\u003eDevice Manager\u003c\/h2\u003e\n\u003cp\u003eDevice Manager software allows to capture data from supported fingerprint readers, iris scanners, cameras and webcams. Integrators can also write plug-ins to support their fingerprint readers, cameras or other devices using the plug-in framework provided with the Device Manager.\u003c\/p\u003e\n\u003ch6\u003eTech Specs\u003c\/h6\u003e\n\u003cp\u003eMegaMatcher On Card can be configured according to different requirements and smart card constraints, at both pure Java Card level and native code. The summary of average memory requirements is available below. The MegaMatcher On Card template matching engines performance was tested for smart cards from several vendors; see the testing results for more information on matching speed for a particular card.\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003e500 ppi\u003c\/strong\u003e is the recommended fingerprint image resolution.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e640 x 480 pixels\u003c\/strong\u003e is the recommended image size for face detection. \u003cstrong\u003e40 pixels\u003c\/strong\u003e is the minimal distance between the eyes for face detection.\u003c\/li\u003e\n\u003cli\u003eMegaMatcher On Card face extraction engine has certain tolerance to face posture that assures face detection:\n\u003cul class=\"complex\"\u003e\n\u003cli\u003ehead \u003cstrong\u003eroll\u003c\/strong\u003e (tilt) – ±15 degrees from frontal position.\u003c\/li\u003e\n\u003cli\u003ehead \u003cstrong\u003epitch\u003c\/strong\u003e (nod) – ±15 degrees from frontal position.\u003c\/li\u003e\n\u003cli\u003ehead \u003cstrong\u003eyaw\u003c\/strong\u003e (bobble) – ±15 degrees from frontal position.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003e640 x 480 pixels\u003c\/strong\u003e is the minimum image size for iris capture. \u003cstrong\u003e±15 degrees\u003c\/strong\u003e is the default iris rotation tolerance; this value can be extended on demand.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp class=\"list_cap\"\u003eBelow are provided the memory requirements for the native level integration and Java Card post-issuance libraries. Note that the Java Card post-issuance libraries utilize Java level RAM for internal matching engine routines, whereas the native level integrations temporary utilize RAM available at the native level while the internal routines run, thus consuming no static Java level RAM.\u003c\/p\u003e\n\u003cdiv style=\"margin: 1em 0em; clear: both;\" align=\"center\"\u003e\n\u003ctable style=\"background-color: #ffffff;\" class=\"data\" width=\"100%\" cellspacing=\"0\" cellpadding=\"0\" border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth colspan=\"4\" align=\"center\"\u003eMegaMatcher On Card (Current Version) memory requirements for native level integration\u003cbr\u003e(maximized accuracy configuration)\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_top\" width=\"37%\"\u003e\u003cbr\u003e\u003c\/td\u003e\n\u003ctd class=\"cap_top\" width=\"21%\"\u003eCode size (kilobytes)\u003c\/td\u003e\n\u003ctd class=\"cap_top\" width=\"21%\"\u003eRequired RAM (bytes)\u003c\/td\u003e\n\u003ctd class=\"cap_top\" width=\"21%\"\u003eTemplate size (bytes)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eFingerprint verification engine\u003c\/td\u003e\n\u003ctd\u003e6.1 - 11.0\u003c\/td\u003e\n\u003ctd\u003e960 - 2,200 \u003csup\u003e(1)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003ctd\u003e660 - 2,100 \u003csup\u003e(1)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eFace verification engine\u003c\/td\u003e\n\u003ctd colspan=\"3\" rowspan=\"3\" valign=\"middle\"\u003eNot implemented\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eIris verification engine\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eMulti-modal verification engines\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp align=\"left\"\u003e\u003csup\u003e(1)\u003c\/sup\u003e Depends on the configurable maximal number of minutiae.\u003c\/p\u003e\n\u003ctable style=\"background-color: #ffffff;\" class=\"data\" width=\"100%\" cellspacing=\"0\" cellpadding=\"0\" border=\"1\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth colspan=\"4\" align=\"center\"\u003eMegaMatcher On Card (Current Version) memory requirements for Java Card post-issuance libraries (maximized speed configuration)\u003c\/th\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_top\" width=\"37%\"\u003e\u003cbr\u003e\u003c\/td\u003e\n\u003ctd class=\"cap_top\" width=\"21%\"\u003eCode size (kilobytes)\u003c\/td\u003e\n\u003ctd class=\"cap_top\" width=\"21%\"\u003eRequired RAM (bytes)\u003c\/td\u003e\n\u003ctd class=\"cap_top\" width=\"21%\"\u003eTemplate size (bytes)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eFingerprint verification engine\u003c\/td\u003e\n\u003ctd\u003eless than 13.3\u003c\/td\u003e\n\u003ctd\u003eless than 600 \u003csup\u003e(1)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003ctd\u003eless than 1,024 \u003csup\u003e(1)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eFace verification engine\u003c\/td\u003e\n\u003ctd\u003eless than 4.4\u003c\/td\u003e\n\u003ctd\u003eless than 16\u003c\/td\u003e\n\u003ctd\u003eless than 2,700 \u003csup\u003e(2)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eIris verification engine\u003c\/td\u003e\n\u003ctd\u003eless than 8.3\u003c\/td\u003e\n\u003ctd\u003eless than 700 \u003csup\u003e(3)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003ctd\u003eless than 1,100 \u003csup\u003e(3)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eBi-modal fingerprint + face verification engine\u003c\/td\u003e\n\u003ctd\u003eless than 16\u003c\/td\u003e\n\u003ctd\u003eless than\u003cbr\u003e600 \u003csup\u003e(1)\u003c\/sup\u003e \u003csup\u003e(2)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003ctd\u003esee specific modalities above\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eBi-modal fingerprint + iris verification engine\u003c\/td\u003e\n\u003ctd\u003eless than 20\u003c\/td\u003e\n\u003ctd\u003eless than\u003cbr\u003e800 \u003csup\u003e(1)\u003c\/sup\u003e \u003csup\u003e(3)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003ctd\u003esee specific modalities above\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eBi-modal face + iris verification engine\u003c\/td\u003e\n\u003ctd\u003eless than 11\u003c\/td\u003e\n\u003ctd\u003eless than\u003cbr\u003e700 \u003csup\u003e(2)\u003c\/sup\u003e \u003csup\u003e(3)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003ctd\u003esee specific modalities above\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd class=\"cap_left\"\u003eTri-modal verification engine\u003c\/td\u003e\n\u003ctd\u003eless than 22\u003c\/td\u003e\n\u003ctd\u003eless than\u003cbr\u003e800 \u003csup\u003e(1)\u003c\/sup\u003e \u003csup\u003e(2)\u003c\/sup\u003e \u003csup\u003e(3)\u003c\/sup\u003e\n\u003c\/td\u003e\n\u003ctd\u003esee specific modalities above\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003cp align=\"left\"\u003e\u003csup\u003e(1)\u003c\/sup\u003e Depends on the configurable maximal number of minutiae. \u003cbr\u003e \u003csup\u003e(2)\u003c\/sup\u003e Using faces compact card template format. \u003cbr\u003e \u003csup\u003e(3)\u003c\/sup\u003e Using irises compact card template format.\u003c\/p\u003e\n\u003c\/div\u003e","brand":"Neurotechnology, Ltd.","offers":[{"title":"Default Title","offer_id":41331021283430,"sku":"100590","price":377.39,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0580\/3812\/4646\/files\/megamatcher-on-card.jpg?v=1714422387"}],"url":"https:\/\/store.fulcrumbiometrics.co.uk\/collections\/all.oembed?page=12","provider":"Fulcrum Biometrics, Limited","version":"1.0","type":"link"}