Iris Segmentation and Normalization Approach

Iris is a desirable biometric representation of an individual for security-related applications. However the iris segmentation and normalization process is challenging due to the presence of eye lashes that occlude the iris, the dilation of pupils due to different light illumination and several other uncontrolled factors. In this work, we enhanced Daugman method to locate the iris and normalized it from polar to Cartesian coordinate. Iris is located by using a variable parameter binning approach. The algorithm is tested using iris images from CASIA database and MMU database. The percentage detection on MMU iris database is 99% and that of CASIA is 98%. Our approach is feasible to produce an iris template for identity identification and biometric watermarking application.