Neurotechnology MegaMatcher update improves algorithms across modalities

Neurotechnology’s updated MegaMatcher products have enhanced algorithms for fingerprint, face, palmprint and iris recognition, according to a press release from the Vilnius-based provider of deep learning-based biometric identification technologies.

The updates apply to the MegaMatcher SDK and MegaMatcher Accelerator products, which use the company’s proprietary biometric recognition technology for use cases in elections, national identity, border control, law enforcement and other government and enterprise applications.

“This MegaMatcher update is a major step forward in providing accurate and flexible biometric solutions to suit a variety of different client needs,” says Irmantas Naujikas, director at Neurotechnology. “The new algorithms, features and supported standards are tailored to address the evolving challenges in biometric identification, offering industry-leading accuracy and reliability to our clients worldwide.”

Per the release, new fingerprint algorithms, tested in NIST MINEX III, ELFT, and PFT III evaluations, “deliver greater overall accuracy.” An updated facial recognition algorithm evaluated in NIST FRVT “introduces a new template size maximizing accuracy for server applications.”

And “the new iris algorithm, designed to perform better with lower-quality iris scans, exhibits increased accuracy and was evaluated in the NIST IREX 10 evaluation.”

Other new features for usability and security include enabling contactless fingerprint capture with a smartphone camera to record four fingerprints simultaneously, finger anomaly detection to analyze the four-finger scan images, face morph detection to identify digitally altered face images, and enhanced compliance with biometric standards.

Article Topics

algorithms  |  biometric identification  |  biometrics  |  MegaMatcher  |  Neurotechnology  |  SDK