Neurotechnology’s Proprietary Fingerprint Technology Regains First Place in NIST PFT III Evaluation
We are proud to announce that our fingerprint recognition algorithm leads the National Institute of Standards and Technology (NIST) Proprietary Fingerprint Template III (PFT III) evaluation. On its main PFT III results page, NIST presents testing results for four datasets: two from criminal investigations and two from border control. Among the participating algorithms, our latest algorithm, Neurotechnology+0011, achieved the lowest FNMR values at nearly all measured FMR values across the datasets, making it the most accurate algorithm in the majority of tests. Our team is pleased with the outcomes and is determined to maintain its position as the industry leader in fingerprint recognition. The evaluation provides an excellent platform for showcasing the benefits of our unique fingerprint recognition technology. Read our press release for more information. Neurotechnology is an active participant in independent technology evaluations, including NIST ELFT, SlapSeg III, MINEX III, FRVT, and IREX 10, where it has proved to be one of the leading contenders over the years.
Neurotechnology’s latest proprietary fingerprint verification algorithm performs best in the majority of tests of the NIST PFT III evaluation.
Neurotechnology, a provider of deep learning-based solutions and high-precision biometric identification technologies, today announced that after just a two-month gap, the company’s proprietary algorithm once again leads the National Institute of Standards and Technology (NIST) Proprietary Fingerprint Template III (PFT III) evaluation.
The NIST PFT III evaluation assesses the performance of fingerprint verification algorithms using vendor-specific templates, enabling participants to demonstrate their proprietary capabilities. The latest results showcase Neurotechnology’s track record of continually developing industry-leading fingerprint technologies.
“The evaluation landscape is dynamic, and it is interesting to see other vendors trying to overtake our top spot in PFT III which we held for several years,” said Evaldas Borcovas, head of biometric technologies research at Neurotechnology. “The evaluation offers a valuable platform to showcase the advantage of our custom fingerprint verification algorithms. Our entire team is proud of the results we have achieved and will continue to be the leading force in fingerprint recognition.”
On its main PFT III results page, NIST presents testing results for four datasets: two from criminal investigations (Arizona Department of Public Safety and Los Angeles County Sheriff’s Department) and two from border control (The Port of Entry/BioVisa Application and The US-VISIT #2). For each dataset, it reports False Non-Match Rates (FNMR) at three distinct False Match Rates (FMR). Among the participating algorithms, Neurotechnology’s latest algorithm, Neurotechnology+0011, achieved the lowest FNMR values at nearly all measured FMR values across the datasets.
Neurotechnology, as a multi-biometric solutions developer, is also an active participant in other NIST evaluations of different biometric modalities. Over the years, the company’s biometric algorithms have achieved top results in independent technology evaluations, including NIST ELFT, SlapSeg III, MINEX III, FRVT, and IREX 10.
About Neurotechnology
Neurotechnology is a developer of high-precision algorithms and software based on deep neural networks and other AI-related technologies. The company was launched in 1990 in Vilnius, Lithuania, with the key idea of leveraging neural network capabilities for various applications, such as biometric person identification, computer vision, robotics, and artificial intelligence. The company’s solutions and products have been used in more than 140 countries worldwide and in many national-scale projects for national ID, passports, elections, and border control, including India’s Aadhaar program, general elections in Ghana and Liberia, voter deduplication for the Democratic Republic of the Congo and other projects that collectively process the biometric data of nearly two billion people.
Credit/Source URL – https://www.neurotechnology.com/press_release_pft_iii_2024.html
