Iris Localization with Dual Coarse-to-fine Strategy

Iris-based personal recognition is highly dependent on the accurate iris localization. In this paper, an effective and efficient iris localization algorithm is proposed to overcome the drawback of the traditional localization methods which are time-consuming and sensitive to the occlusion caused by eyelids and eyelashes. The coarse-to-fine strategy is deployed in both the inner boundary localization and the outer boundary localization. In the coarse localization of the inner boundary, the lower contour of the pupil is introduced to estimate the parameters of the pupil since it is stable even when the iris image is seriously occluded. While in the coarse localization of the outer boundary, the average intensity signals on both sides of the pupil are utilized to estimate the parameters of the sclera after the fine localization of the inner boundary. In the fine stage, the Hough transform is adopted to localize both boundaries precisely with the gradient information. Experimental results indicate that the proposed method is more effective and efficient