[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5391/IJFIS.2002.2.3.227

Iris Segmentation and Recognition

Kim, Jae-Min (School of Electronics and Electrical Engineering, Hongik University)
Cho, Seong-Won (School of Electronics and Electrical Engineering, Hongik University)

Publication Information

International Journal of Fuzzy Logic and Intelligent Systems / v.2, no.3, 2002 , pp. 227-230 More about this Journal

Abstract

A new iris segmentation and recognition method is described. Combining a statistical classification and elastic boundary fitting, the iris is first segmented robustly and accurately. Once the iris is segmented, one-dimensional signals are computed in the iris and decomposed into multiple frequency bands. Each decomposed signal is approximated by a piecewise linear curve connecting a small set of node points. The node points represent features of each signal. The similarity measture between two iris images is the normalized cross-correlation coefficients between simplified signals.

Keywords

iris segmentation; iris recognition; wavelet transform; expectation-maximization algorithm; active contour model;

Citations & Related Records

Reference

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