Iris Segmentation using Adaptive Histogram Equalization and Median Filtering

The personal identification based on Iris biometric is one of the most suitable and reliable methods with respect to performance and accuracy. However, the reliability and accuracy of the method depends on the proper segmentation of an iris from an eye image. In this paper, Adaptive Histogram Equalization (AHE) and median filtering are employed to segment the iris region from an eye image. Segmented iris patterns are classified using ANN. The experiments are performed over CASIA iris V3 interval database obtained from public domain digital repository. The experimental results demonstrate that the proposed approach outperforms the existing approaches, viz. Daugman's approach, Masek's approach and Abdullah's approach in terms of running time and image classification accuracy for the considered dataset.