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Author Kong, Adams ♦ Zhang, David ♦ Kamel, Mohamed
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Rapid Matching ♦ Iris Recognition Algorithm ♦ Binomial Distribution ♦ Angular Distance ♦ Theoretical Foundation ♦ Theoretical Analysis ♦ Two-dimensional Ellipse ♦ Considerable Attention ♦ Imposter Distribution ♦ Precise Phase Representation ♦ Gabor Function ♦ Theoretical Evidence ♦ Phase Parameter ♦ Binomial Imposter Distribution ♦ Predictable False Acceptance Rate ♦ Coarse Phase Representation ♦ Effective Implementation ♦ Bitwise Hamming
Description IrisCode, a widely deployed iris recognition algorithm, developed in 1993 and continuously modified by Daugman has attracted considerable attentions. IrisCode using a coarse phase representation has number of properties such as rapid matching, binomial imposter distribution and predictable false acceptance rate. Although many similar coding methods have been developed for irises and palmprints based on IrisCode, a theoretical analysis of IrisCode has not been provided. In this paper, we aim at studying (1) the nature of IrisCode, (2) the property of the phase of Gabor function, (3) the extension of bitwise hamming distance and (4) the theoretical foundation of the binomial imposter distribution and extending the coarse phase representation to a precise phase representation. Precisely, we demonstrate that IrisCode is a clustering algorithm with four prototypes; the locus of a Gabor function is a two-dimensional ellipse with respect to the phase parameter and bitwise hamming can be regarded as angular distance. Using these properties, we provide a precise phase representation for IrisCode with an effective implementation for filtering and matching. Practically, the imposter distribution of IrisCode follows binomial distribution. However, the theoretical evidence is incomplete according to our analysis. 1.
In Int. Conf. on Pattern Recognition
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2006-01-01