Modeling and simulation of intelligent vision based pattern-recognition of Colour-Iris

Abstract

Among the several algorithms that exist for Iris pattern recognition, Daugman’s innovation is one of the most implemented approaches. His algorithm is based on Near-InfraRed (NIR) images which have been proven as an effective technique particularly when used in controlled scenarios [1]. The trend of using gray NIR-base images then dominates the process of Iris recognition and influences the majority of eyes’ images databases. The aim of this paper is to create a model that achieves a more effective Iris-recognition system (i.e. Iris encoding and recognition) by considering the individualities of both the pattern-structure and Colour of the Iris-pattern. The conducted simulation shows positive results. Via colour analysis, the model can efficiently and accurately divide all suspect samples into a small group. The recognition system then searches and compares within a smaller quantity of suspected samples. This case has shown that the model can increase the recognition speed up to 70% [6]. In the proposed circumstances, this model also supports the accuracy of Iris recognition.