Enhancement of pupil detection and performance comparison based on different iris pattern

In this research, the effectiveness of fusion due to profile and mask as detection of pupil is investigated. Next, upon completion of pupil detection, the capability of iris recognition based on half size and full size iris is validated with 2D log Gabor as feature encoding, Support Vector Machine as classifier along with Bath Iris Image as the chosen database. Initial findings showed that fusion of profile and mask technique require least computational time for pupil detection. In addition, half iris code size is apt for recognition as compared to the whole iris image due to lower False Acceptance Rate and higher False Rejection Rate attained along with optimum Success Rate.