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Author(s): |
Jun Zhou, Dept. of Training, Logistical Engineering University, Chongqing, China
Ting Luo, Dept. of Training, Logistical Engineering University, Chongqing, China
Min Li, Dept. of Training, Logistical Engineering University, Chongqing, China
Shijun Guo, Dept. of Training, Logistical Engineering University, Chongqing, China
Taiping Qing, Dept. of Training, Logistical Engineering University, Chongqing, China |
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Abstract: |
Iris feature extraction is a process which converts the change of iris texture to comparable mathe- matical characterization. [1 The performance of iris recognition system is determined largely by the iris feature extraction algorithm. To improve the accuracy of iris recognition system, we propose an efficient algorithm for iris feature extraction based on 2D Haar wavelet. Firstly, the iris image is decomposed by the 2D Haar wavelet three times, and then a 375-bit iris code is obtained by quantizing all the high-frequency coefficients at third lever. Finally we use similarity degree function as matching scheme. Experimental results on CASIA iris database show that our algorithm has the encouraging correct recognition rate (CRR) which is only 99.18%, accompanying with very low equal error rate (EER).The proposed algorithm yields attractive per- formances and comparable to the best iris recognition algorithm found in the current literature. Comparing with Boles’ method and Lim’s method which is based on wavelet transform, our algorithm shows better per- formance.
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