Solution Helps Reduce Fingerprint Software False Reject Rates

M2SYS, a biometric technology research and development firm, recently released Bio-AI. The artificial intelligence enhancement uses a unique "dynamic profiling" technique to learn about a person's fingerprints over time. This knowledge enables the fingerprint software to take actions that mitigate the chance of generating a false reject following a fingerprint scan.

A false reject (or false negative) in terms of biometric technology occurs when the system fails to identify a successfully enrolled user. In other words, although a biometric template exists for the user that is attempting to be identified, the biometric system returns a "no match found" result, and user authentication is denied.

The probability that a biometrics system will produce a false reject is known as the false reject rate (FRR). The FRR is a critical variable involved in the successful selection and deployment of a fingerprint identification system. False rejects are extremely frustrating, and can also lead to increased costs and decreased productivity for companies that have invested in fingerprint biometrics.

Through constant communication with thousands of end user deployments over many vertical markets, M2SYS was able to recognize the real-world benefit of a solution to the false reject problem. The installation of Bio-AI reduces the need for users to perfectly align their finger during identification scans, which improves usability and increases the likelihood of a fingerprint match. Production deployments of Bio-AI have already shown very high success rates.

"False rejects are a common but very serious issue across the entire biometrics industry," said Mizan Rahman, CEO and chief scientist of M2SYS. "Undeservedly being unable to clock in for work or being denied the ability to pick up your child from daycare can have serious consequences. With Bio-AI(TM), M2SYS is again solving a vital issue in fingerprint biometrics."

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