Eyelid and Eyelash Occlusions Detection for Iris Recognition

Two gray-scale morphological algorithms are presented for the detection of eyelid and eyelash occlusions based on intensity and shape information.Firstly,an arc morphological structuring element is designed for detecting eyelid edge.A set of candidate points for eyelid edge can be obtained by gray-scale morphological opening,image segmenting,and edge detecting.Then the eyelid edge is fitted on the basis of Bézier curves.Secondly,a crossed morphological structuring element is developed.An iris image,whose intensity is mostly distributed in several sections,can be acquired after gray-scale morphological opening. Thus a binary image of eyelashes is obtained.The experimental results show that the proposed algorithms are effective on detecting these two kinds of occlusion noises,and helpful to reduce the Equal Error Rate of iris recognition system,and finally able to improve the discriminability of iris patterns.