Eyelid localization in iris images captured in less constrained environment

Abstract

Eyelid localization plays an important role in an accurate iris recognition system. In less constrained environment where the subjects are less cooperative, the problem becomes very difficult due to interference of eyelashes, eyebrows, glasses, hair and diverse variation of eye size and position. To determine upper eyelid boundary accurately, the paper proposes an integro-differential parabolic arc operator combined with a RANSAC-like algorithm. The integro-differential operator works as a parabolic arc edge detector. During search process of the operator, the potential candidate parabolas should near at least certain percentage of edgels of upper eyelid boundary, detected by 1D edge detector. The RANSAC-like algorithm functions as a constraint that not only makes eyelid localization more accurate, but also enables it more efficient by excluding invalid candidates for further processing. Lower eyelid localization is much simpler due to very less interference involved, and a method is presented that exploits 1D edgels detection and an RANSAC algorithm for parabolic fitting. Experiments are made on UBIRIS.v2 where images were captured at-a-distance and on-the-move. The comparison shows that the proposed algorithm is quite effective in localizing eyelids in heterogeneous images. © Springer-Verlag Berlin Heidelberg 2009.