VILNIUS, Lithuania, Feb. 12, 2019 /PRNewswire/ -- Neurotechnology, a provider of deep learning-based solutions, robotics and high-precision biometric identification technologies, today reported the latest FVC-onGoing test results for their Palm Print recognition algorithm. Palm Print, part of Neurotechnology's MegaMatcher SDK, was ranked as the most accurate for both full and partial palm prints, as the fastest partial palm print matcher and the fastest full-print matcher out of the five most accurate matchers. Neurotechnology's algorithm also has the smallest template size overall, both in full palm print and partial (lower) palm print datasets.

"Our expertise in fingerprint recognition technologies carries over to palm print matching," said Dr. Justas Kranauskas, head of the biometric research department for Neurotechnology. "Though the palm print is a larger, more detailed recognition task, our experience in this field allows us to bring the most accurate, highest efficiency application available to the palm print recognition market."

Because of its complexity, palm print template matching requires much more computational time than single or multiple fingerprint matching. Focusing on speed, as well as accuracy, Neurotechnology has developed a palm print matching algorithm that is the fastest partial (lower) palm print matcher and fastest full palm print matcher out of the top five most accurate full palm print matchers in FVC-onGoing. It is suitable for both 1-to-1 (verification) and 1-to-many (identification) applications.

Neurotechnology's palm print matching engine is included in MegaMatcher Standard and Extended SDKs.

MegaMatcher SDKs, and the entire Neurotechnology biometric product line, can be purchased from Neurotechnology and through distributors worldwide. A free 30-day trial is available and, as with all Neurotechnology products, the latest version is a free upgrade for existing customers.

For more information, go to www.neurotechnology.com.

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 using neural networks for various applications, such as biometric person identification, computer vision, robotics and artificial intelligence. Since the first release of its fingerprint identification system in 1991, the company has delivered more than 200 products and version upgrades. More than 3,000 system integrators, security companies and hardware providers in more than 140 countries integrate Neurotechnology's algorithms into their products. The company's algorithms have achieved top results in independent technology evaluations, including NIST MINEX and IREX. www.neurotechnology.com

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SOURCE Neurotechnology