Large-scale AFIS and multi-biometric identification
MegaMatcher 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.
Available 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, macOS, iOS and Android platforms.
MegaMatcher technology has received numerous awards and compliancy certifications from government and science authorities.
MINEX evaluations by NIST
- MINEX III evaluation was successfully passed in 2015. In 2019 Neurotechnology's fingerprint template generator algorithm has been ranked the first in the NIST MINEX interoperability category; the fingerprint matching algorithm has also been ranked as the front-runner in terms of interoperability and, when combined, the two have become the supreme accuracy, high speed fingerprint recognition system. See our comments on MINEX III participation for more details about the results.
- MINEX Ongoing evaluation was successfully passed in 2014. The second place in the Ongoing MINEX ranking for fingerprint matching algorithms was achieved. MegaMatcher technology was recognized by the NIST as fully MINEX compliant. Read more.
- In 2020 MegaMatcher fingerprint recognition algorithm has shown the top result at the FVC-onGoing evaluation. The fingerprint extractor and matcher were ranked as the most accurate for both FV-STD-1.0 and FV-HARD-1.0 benchmarks. Our press release has more information.
- In 2019 MegaMatcher palm print matching algorithm has shown the top result at the FVC-onGoing evaluation. The algorithm was the most accurate overall and fastest among the five most accurate matchers. See our press release for more information.
PFT II and PFT III (Proprietary Fingerprint Template) Evaluations
Different versions of Neurotechnology's fingerprint recognition algorithm were submitted to the NIST Proprietary Fingerprint Template Evaluation. The algorithm's template matching accuracy was among the best participants at the previous PFT II evaluation. Our latest submissions to the PFT II and the ongoing PFT III are in average the most accurate algorithms in all the experiments. See our comments for more information.
SlapSeg III Evaluation
Neurotechnology's slap fingerprint segmentation algorithm has been judged by NIST as the most accurate among the SlapSeg III 2 inch category participants. See our comments for more information.
FpVTE (Fingerprint Vendor Technology Evaluations) by NIST
- FpVTE 2012 – in 2015 NIST recognized Neurotechnology's fingerprint identification algorithm as one of the fastest and most accurate among the evaluation's participants. See our comments on FpVTE 2012 participation for more details about the results.
- FpVTE 2003 – one of the best reliability results in the Middle Scale Test were shown. Neurotechnology participated in FpVTE 2003 under the name Neurotechnologija. See the FpVTE 2003 web site for a detailed report of the evaluation results.
IREX evaluations by NIST
- IREX 10 – in 2020 Neurotechnology's iris recognition algorithm has been judged by NIST as the second most accurate among the IREX 10 participants. The submitted algorithm featured much faster template creation and search time, and much smaller template size than the only more accurate contender. See our comments on IREX 10 participation for more details.
- IREX IX – in 2018 Neurotechnology's iris recognition algorithm has been judged by the NIST as the second most accurate among the participants. The accelerated version of the algorithm was nearly 50 times faster than any other matcher in the NIST IREX IX evaluation. See our comments on IREX IX participation for more details.
- IREX IV – in 2013 Neurotechnology's iris recognition algorithm has been judged the by the NIST as one of the fastest and most accurate among the participants. See our comments on IREX IV participation for more details.
- IREX III – in 2012 MegaMatcher iris matching algorithm was the second fastest and provided 3 times higher recognition accuracy than the only faster contender. Read more.
In 2018 Neurotechnology has been ranked among 8 most accurate face recognition algorithm vendors out of 39, with tenth most accurate algorithm out of 78 in the FRVT leaderboard. The submission was also ranked as one of the best in two difficult scenarios, with second most accurate result on a complex dataset collected from operational photos related to ongoing criminal investigations, and fourth most accurate result with unconstrained, photojournalism-style photos. Our comments on FRVT participation contain more details about the results.
FIVE (Face in Video Evaluation)
In 2015 Neurotechnology face recognition engine to the NIST Face in Video Evaluation (FIVE). In average the submitted algorithm was ranked among top 8 most accurate face recognition algorithms out of 16 vendors. See our comment for more information.
WSQ 3.1 Certification by the FBI
In 2011 FBI certified Neurotechnology's implementation of WSQ image format support. Certificates and additional information are available.