Open AccessSearching for doppelgängers: assessing the universality of the IrisCode impostors distribution
Author(s) -
Daugman John,
Downing Cathryn
Publication year - 2016
Publication title -
iet biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 28
ISSN - 2047-4946
DOI - 10.1049/iet-bmt.2015.0071
Subject(s) - biometrics , computer science , quantile , standard deviation , artificial intelligence , population , entropy (arrow of time) , statistics , pattern recognition (psychology) , mathematics , medicine , physics , environmental health , quantum mechanics
The authors generated 316,250 entire distributions of IrisCode impostor scores, each distribution obtained by comparing one iris against hundreds of thousands of others in a database including persons spanning 152 nationalities. Altogether 100 billion iris comparisons were performed in this study. The purpose was to evaluate whether, in the tradition of Doddington's Zoo, some individuals are inherently more prone than most to generate iris false matches, while others are inherently less prone. With the standard score normalisation disabled, a detailed inter‐quantile analysis showed that meaningful deviations from a universal impostors distribution occur only for individual distributions that are highly extreme in both their mean and their standard deviation, and which appear to make up <1% of the population. In general, when different persons are compared, the IrisCode produces relatively constant dissimilarity distances having an invariant narrow distribution, thanks to the large entropy which lies at the heart of this biometric modality. The authors discuss the implications of these findings and their caveats for various search strategies, including ‘1‐to‐first’ and ‘1‐to‐many’ iris matching.