An Improved Approach for IRIS Authentication System by Using Daugman’s Rubber Sheet Model, Segmentation, Normalization and RSA Security Algorithm

This paper combines different modules to improve the performance of an iris reorganization system. Iris is emerging as one of the important methods of biometrics-based identification systems. This iris system consisted of major components: image preprocessing, segmentation, edge detection, normalization, pattern matching and encryption decryption, as project basically explains the Iris recognition system developed by John Daugman and attempts to implement RSA algorithm in Java, with a few modifications. Firstly, image preprocessing is performed followed by extracting the iris portion of the eye image. The edge information is detected by four different directional line detectors. Significant edges are then selected using an adaptive thresholding technique, called quotient thresholding. The extracted iris part is then normalized, and Iris Code is constructed. Experimental image results show that unique codes can be generated for every eye image. In this context, different noisy and artificial iris images are analysed in this paper in order to determine its influence in iris recognition systems performance. Finally RSA security algorithm improves the security of the system.