Improvement of Iris Recognition Based on Iris-Code Bit-Error Pattern Analysis

In this paper an advanced iris-biometric comparator is presented. In the proposed scheme an analysis of bit-error patterns produced by Hamming distance-based iris-code comparisons is performed. The lengths of sequences of horizontal consecutive mis-matching bits are measured and a frequency distribution is estimated. The difference of the extracted frequency distribution to that of an average genuine one obtained from a training set is used as a second comparison score. This score is then used together with the fractional Hamming distance in order to improve the recognition accuracy of an iris recognition system. In experimental evaluations relative improvements of approximately 45% and 10% in terms of false non-match rate at a false match rate of 0.01% are achieved on the CASIAv4-Interval and the BioSecure iris databases, respectively.

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