| Summary: | In order to improve recognition accuracy of iris recognition，the iris image was disposed,as the result the iris region of image was accurately located and the normalized image was enhanced. The Haar wavelet transform was used in the feature extraction and K-means was used to cluster the feature,so that a small sample set of iris images was obtained.Combined with iris texture characteristics,the features were extracted by using Log-Gabor filter and the iris feature template was formed after quantization coding. The similarity of iris feature template was calculated by Hamming distance in small sample set, and the iris recognition was completed. The testing results illustrate that the proposed algorithm has a certain improvement in recognition accuracy and effectively avoids the problem of large amount of computation and long time in iris matching because of the variety and quantity of iris database.
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