Image understanding for iris biometrics: A survey
Computer Vision and Image Understanding
A novel iris segmentation using radial-suppression edge detection
Signal Processing
Iris segmentation in non-ideal images using graph cuts
Image and Vision Computing
Edge curvature and convexity based ellipse detection method
Pattern Recognition
Fast algorithm for iris detection
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
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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.