How Iris Recognition Works

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How Iris Recognition Works (2003)

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by John Daugman

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490 - 4 self

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@MISC{Daugman03howiris,
    author = {John Daugman},
    title = {How Iris Recognition Works},
    year = {2003}
}

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Abstract

Algorithms developed by the author for recogniz-ing persons by their iris patterns have now been tested in six field and laboratory trials, producing no false matches in several million comparison tests. The recognition principle is the failure of a test of statis-tical independence on iris phase structure encoded by multi-scale quadrature wavelets. The combinatorial complexity of this phase information across different persons spans about 244 degrees of freedom and gen-erates a discrimination entropy of about 3.2 bits/mm over the iris, enabling real-time decisions about per-sonal identity with extremely high confidence. The high confidence levels are important because they al-low very large databases to be searched exhaustively (one-to-many “identification mode”) without making any false matches, despite so many chances. Biomet-rics lacking this property can only survive one-to-one (“verification”) or few comparisons. This paper ex-plains the algorithms for iris recognition, and presents the results of 2.3 million comparisons among eye im-ages acquired in trials in Britain, the USA, and Japan. 1

Keyphrases

iris recognition work false match comparison test statis-tical independence multi-scale quadrature wavelet recognition principle discrimination entropy high confidence phase information high confidence level iris phase structure recogniz-ing person iris recognition different person span large database many chance combinatorial complexity one-to-many identification mode per-sonal identity iris pattern eye im-ages real-time decision laboratory trial

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