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Blog Category: Biometrics

NIST: Iris Recognition Report Evaluates 'Needle in Haystack' Search Capability

Image of human eye/iris (Photo: Talbott/NIST)

Identifying people by acquiring pictures of their eyes is becoming easier, according to a new report from Commerce's National Institute of Standards and Technology (NIST). NIST researchers evaluated the performance of iris recognition software from 11 different organizations and found that some techniques produced very rapid results—though this speed was often at the cost of accuracy.

Iris recognition, a form of biometric identification based on noncontact imaging of the complex texture in an individual's iris, has been purported to be both fast and accurate—claims that had not been validated until now. The Iris Exchange (IREX) III report is the first public and independent comparison of commercially available algorithms that use iris recognition for the challenging task of finding an individual match within a large database of potential identities. Previous published studies only used single algorithms or considered "one-to-one" verification, in which an individual claims an identity and the software then attempts to confirm whether the claim matches a specific record.

Global Biometric Leaders Attend International Biometric Performance Conference at NIST

image of thumb print

Anyone who enjoys police dramas on TV knows that biometrics such as fingerprints and DNA are used to match criminals to crimes. But increasingly, biometrics are being used in public and private arenas to ensure access to computers and buildings, or to authenticate that you are really you when traveling internationally with an e–passport. One day, biometrics may be used to authenticate who you are when banking or buying something on the Internet.

Last week, biometric experts from across the globe have been attending the International Biometric Performance Conference at Commerce's National Institute of Standards and Technology (NIST) in Gaithersburg, Md. This applied research conference was focused on identifying fundamental, relevant, effective and new performance metrics for biometric systems and determining and sharing best practices for performance evaluation and calibration as they relate to design specifications and day-to-day operations. The goal is for people and computer systems to know reliably who is who.