Improved Normalization Approach for Iris Image Classification Using SVM

With the rapid improvement of information technology, security and authentication of individuals have become a greater significance. Iris recognition is one of the best solutions in providing unique authentication for individuals based on their IRIS structure. Iris normalization is meant to extract the iris region and represent it in the spatial domain, Daugman’s rubber sheet model is so far a standard and efficient method of implementing this process. In this paper, a low complex, simpler and improved version of rubber sheet model is proposed. The main aim of this method is to minimize the complex computations that were involved in the conventional rubber sheet model and to provide an equivalent performing approach with very less computations. Classification performance is evaluated with CASIA and IIT Delhi IRIS databases using SVM classifier.