Automated algorithm for iris detection and code generation

The interface of computer technologies and biology is having a huge impact on society. Human recognition research projects promises new life to many security-consulting firms and personal identification system manufacturers. Iris recognition is considered to be the most reliable biometric authentication system. Very few iris recognition algorithms were commercialized. The method proposed in this paper differed from the existing work in the iris segmentation and feature extraction phase. Digitized grayscale images of Chinese Academy of Sciences-Institute of Automation (CASIA) database were used for determining the performance of the proposed system. The circular iris and pupil of the eye image were segmented using morphological operators as well as circular Hough transform. The localized iris region was then normalized into a rectangular block to account for imaging inconsistencies. Finally, the corresponding iris code was generated using the Euclidean distance. This method provides accurate signature as well as accurate code of the human iris in a simple and fast way.