Abstract
In this paper we proposed an improved novel approach to identify the person using iris recognition technique. This approach is based on Artificial Neural Network and Support Vector Machine (SVM) as an iris pattern classifier. Prior to classifier, region of interest i.e. iris region is segmented using Canny edge detector and Hough transform. Provided that the effect of eyelid and eyelashes get reduced. Daugman's rubber sheet model used to get normalized iris to improve computational efficiency and proper dimensionality. Further, discriminating feature sequence is obtained by feature extraction from segmented iris image using 1D Log Gabor wavelet. Encoding is done using phase quantization to get feature vectors. These binary sequence feature vectors are used to train SVM and ANN as iris pattern classifier. The experimental tests are performed over standard CASIAIrisV4 database.
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