Face Matching is Only the Start: Key Technologies in Remote Identity Verification
(This is Part 2 of the series about remote identity verification solutions and how to successfully integrate them ...
Read moreInnovatrics’ latest submission to the NIST ELFT benchmark confirms its latent fingerprint algorithm is the most accurate in the world, outperforming all competition in rank-based search. Furthermore, Innovatrics has also scored exceptionally well in the so-called “lights-out” searches.
Innovatrics reached the top with a rank-5 hit rate of 97.5% in FBI – Provided Solved dataset #1, surpassing the competition. This can be seen in the chart from the NIST ELFT Innovatrics nutrition report as of July 16th 2024. Additionally, Innovatrics was evaluated as the most accurate algorithm in rank-based search over the newly added and largest DoD dataset #1, further emphasizing the company’s position as a leading provider of biometric solutions.
Innovatrics has also achieved a further improvement in the so-called “lights-out” searches, a category where a threshold is used to filter out non-matching candidates. A higher threshold likely corresponds with fewer subjects for manual review, which saves the operator some time. Innovatrics is top ranked with over 91% Rank-100 Hit Rate at FPIR = 1%, it means that accuracy remains very high even if 99% of false matches are automatically eliminated.
The term “lights-out” for AFIS has been around for many years and is generally understood to mean “no human intervention is involved”. A lights-out search in the NIST ELFT framework refers to an automated fingerprint examination process, where a computer system autonomously compares a latent fingerprint against a large database without human intervention during the initial stages of analysis. “Lights-out” searches use a threshold to filter out more than 90% of non-matching candidates. A higher threshold likely corresponds with fewer subjects for manual review, which enables the operator to clear the backlog faster. This is also NIST’s preferred accuracy metric because operating costs grow with the rate of these two errors.
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