The 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.

Proprietary image quality control may be applied to accept only good quality fingerprint images.

The component can generalize a fingerprint template from several images that contain the same fingerprint to improve the template's quality.

The 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.

Fingerprint 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:

Left Slant Loop;
Right Slant Loop;
Tented Arch;
Whorl;
Scar;
"Unknown" – for the nondetermined classes.

The 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.

Neurotechnology proprietary fingerprint template format
BioAPI 2.0 (ISO/IEC 19784-1:2006) (Framework and Biometric Service Provider for fingerprint identification engine)
CBEFF V1.2 (ANSI INCITS 398-2008) (Common Biometric Exchange Formats Framework)
CBEFF V2.0 (ISO/IEC 19785-1:2006 with Amd. 1:2010, 19785-3:2007 with Amd. 1:2010) (Common Biometric Exchange Formats Framework)
CBEFF V3.0 (ISO/IEC 19785-3:2015) (Common Biometric Exchange Formats Framework)
ISO/IEC 19794-2:2005 with Cor. 1:2009 (Biometric Data Interchange Formats – Finger Minutiae Data (General Record and On-Card Formats)
ISO/IEC 19794-2:2011 with Cor. 1:2012 (General Record and On-Card Formats) and Amd.2:2015 (XML encoding and clarification of defects)
ISO/IEC 19794-4:2005 with Cor. 1:2011 (Biometric Data Interchange Formats - Finger Image Data)
ISO/IEC 19794-4:2011 with Cor. 1:2012 (Biometric Data Interchange Formats - Finger Image Data)
ISO/IEC 29794-1:2016 (Biometric sample quality)
ANSI/INCITS 378-2004 (Finger Minutiae Format for Data Interchange)
ANSI/INCITS 378-2009 with Amd. 1:2010 (Finger Minutiae Format for Data Interchange)
ANSI/INCITS 381-2004 (Finger Image-Based Data Interchange Format)
ANSI/INCITS 381-2009 with Amd. 1:2011 (Finger Image-Based Data Interchange Format)
ANSI/NIST-CSL 1-1993 (Data Format for the Interchange of Fingerprint, Facial, & SMT Information)
ANSI/NIST-ITL 1a-1997 (Data Format for the Interchange of Fingerprint, Facial, & SMT Information)
ANSI/NIST-ITL 1-2000 (Data Format for the Interchange of Fingerprint, Facial, & SMT Information)
ANSI/NIST-ITL 1-2007 (Data Format for the Interchange of Fingerprint, Facial, & Other Biometric Information)
ANSI/NIST-ITL 1a-2009 (Data Format for the Interchange of Fingerprint, Facial, & Other Biometric Information)
ANSI/NIST-ITL 1-2011 (Data Format for the Interchange of Fingerprint, Facial, & Other Biometric Information)
ANSI/NIST-ITL 1-2011 Update:2013 Edition 2 (Data Format for the Interchange of Fingerprint, Facial, & Other Biometric Information)
ANSI/NIST-ITL 1-2011 Update:2015 (Data Format for the Interchange of Fingerprint, Facial, & Other Biometric Information)

The 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.

The Fingerprint Image Processing component also includes advanced image formats support modules:

JPEG 2000 image format support module with 1000 ppi Fingerprint Profile;
NIST IHead image format support module;
module with NIST Fingerprint Image Quality (NFIQ) algorithm, a standard method to determine fingerprint image quality.
WSQ (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.
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.

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