Meta-analysis of third-party evaluations of iris recognition

Authors:
Elaine M. Newton;P. Jonathon Phillips
Affiliations:
National Institute of Standards and Technology, Gaithersburg, MD;National Institute of Standards and Technology, Gaithersburg, MD
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special section: Best papers from the 2007 biometrics: Theory, applications, and systems (BTAS 07) conference
Year:
2009

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Abstract

Iris recognition has long been widely regarded as a highly accurate biometric despite the lack of independent large-scale testing of its performance. Recently, however, three third-party evaluations of iris recognition were performed. This paper compares and contrasts the results of these independent evaluations. We find that despite differences in methods, hardware, and/or software, all three studies report error rates of the same order of magnitude: observed false nonmatch rates from 0.0122 to 0.03847 at a false match rate of 0.001. Furthermore, the differences between the best performers' error rates are an order of magnitude smaller than the observed error rates.