Efficient Iris Segmentation Based on Eyelid Detection

This paper proposes a computationally efficient eyelid detection algorithm for detecting eyelid boundaries in iris images acquired under less constrained imaging conditions. The proposed eyelid detection algorithm is developed based on the live-wire technique. The major advantage of the proposed algorithm is its computational simplicity as compared to the prior eyelid detection algorithms. The saturation color features of the sclera region of the HSI color space of the iris image are exploited to determine the two intersection points between each eyelid and the outer iris boundary. The strongly connected edges between these two points are detected using the live wire technique that is likely to be the eyelid boundary. The experimental results obtained from UBIRIS.v1 database reveal that the eyelid detection algorithm which proposed in this paper improves the segmentation accuracy for the less constrained iris images.