Human Eye Iris Recognition Using Discrete 2d Reverse Biorthogonal Wavelet 6.8

Abstract Based on unique features possessed by an individual the biometric system provides automatic identification of the person. There have been various implementations using biometric especially for identification and verification cases. In general typical iris recognition follows the approach of image processing and computer vision. This approach contains various stages-image segmentation image normalization feature extraction and image recognition. Iris Biometry has been proposed as sound measure. In this paper an iris recognition system is presented with four steps. First image segmentation is performed using Canny Edge Detector followed by iris Circular Hough transformation CHT and is able to localize the iris and pupil regions. The segmented iris is further normalized. Then features are extracted using discrete 2D reverse biorthogonal wavelet 6.8. Finally the iris codes are compared. The proposed system gives a high recognition rate of 99.82 whereas the FAR and FRR values are calculated the lowest as compared to existing systems. The proposed method is simple and effective. The system is implemented in MATLAB.