Dual iris authentication system using dezert smarandache theory

Abstract

In this paper, a dual iris authentication using Dezert Smarandache theory is presented. The proposed method consists of three main steps: In the first one, the iris images are segmented in order to extract only half iris disc that contains relevant information and is less affected by noise. For that, a Hough transform is used. The segmented images are normalized by Daugman rubber sheet model. In the second step, the normalized images are analyzed by a bench of two 1D Log-Gabor filters to extract the texture characteristics. The encoding is realized with a phase of quantization developed by J. Daugman to generate the binary iris template. For the authentication and the similarity measurement between both binary irises templates, the hamming distances are used with a previously calculated threshold. The score fusion is applied using DSmC combination rule. The proposed method has been tested on a subset of iris database CASIA-IrisV3-Interval. The obtained results give a satisfactory performance with accuracy of 99.96%, FAR of 0%, FRR of 3.89%, EER of 2% and processing time for one iris image of 12.36 s.<em> </em>

Eyelids, eyelashes detection algorithm and houghtransform method for noise removal in iris recognition

“…In recent years, the technology which is based on biometric identification got an instant development. Due to its high reliability, noncontact and some other advantages, iris recognition technology has widely acceptable [1][2][3][4][5][6][7][8][9]. Iris recognition is a method of biometric authentication, based on extracted features of the iris of an individual's eyes [1][2][3].…”