Iris pattern recognition using fuzzy LDA method

Authors:
Hyoun-Joo Go;Keun-Chang Kwak;Mann-Jun Kwon;Myung-Geun Chun
Affiliations:
School of Electrical and Computer Engineering, Chungbuk National University, Cheongju, Korea;School of Electrical and Computer Engineering, Chungbuk National University, Cheongju, Korea;School of Electrical and Computer Engineering, Chungbuk National University, Cheongju, Korea;School of Electrical and Computer Engineering, Chungbuk National University, Cheongju, Korea
Venue:
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Year:
2005

Citing 3
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Abstract

This paper proposes an iris pattern recognition algorithm as one of biometric techniques applied to identify a person using his/her physiological characteristics. Since the iris pattern of human eye has an unique and invariant texture, we can use it as a biometric key. First, we obtain the feature vector from the fuzzy LDA after performing 2D Gabor wavelet transform. And then, we compute the similarity measure based on the correlation. Here, since we use four matching values obtained from four different directional Gabor wavelets and select the maximum value among them, it is possible to reduce the recognition error. To show the usefulness of the proposed algorithm, we applied it to an iris database consisting of 300 iris patterns extracted from 50 subjects and finally got more higher than 90% recognition rate.