A Robust Iris Localization Method Using an Active Contour Model and Hough Transform

Iris segmentation is one of the crucial steps in building an iris recognition system since it affects the accuracy of the iris matching significantly. This segmentation should accurately extract the iris region despite the presence of noises such as varying pupil sizes, shadows, specular reflections and highlights. Considering these obstacles, several attempts have been made in robust iris localization and segmentation. In this paper, we propose a robust iris localization method that uses an active contour model and a circular Hough transform. Experimental results on 100 images from CASIA iris image database show that our method achieves 99% accuracy and is about 2.5 times faster than the Daugman's in locating the pupillary and the limbic boundaries.