An Algorithm for Human Iris Template Matching

Iris recognition systems are widely used in biometrical based technology for personal identification and verification. Many systems have been implemented and their performances have been tested; each of them has its own advantages and disadvantages. In order to get over the drawbacks of these systems mixed techniques were described to implement an iris recognition system. The circular iris and pupil were segmented using threshold concepts and a canny edge detector followed by Circular Hough transform (CHT). Localized iris was normalized by Daugman's rubber sheet model. The coding method based on 1D log-Gabor transform is used to extract the discriminating features. Finally Hamming Distance (HD) operator was used in the template matching process. The proposed system was tested on CASIA database version-1. The results obtained for the hamming distance shows a significant improvement in HD operator as well as the processing time.