An Approach for Secure Identification and Authentication for Biometrics using Iris

Abstract

One of the most accurate biometric authentication methods is iris pattern recognition. Basically iris recognition is a method of biometric recognition and authentication that uses recognition strategies on images of a people eyes. This paper presents a secure authentication using iris recognition system. A usual recognition system has distinctive phases like enrollment phase and authentication phase. In this proposed work CASIA V4 iris is considered as a database. The flow of work starts with pre-processing, feature extraction and classification. This procedure is implemented using evaluation of various iris pattern recognition features by using Histogram of Oriented Gradients (HOG), Gray Level Co-occurrence Matrix (GLCM), Hausdroff Dimensions (HD), Biometric Graph Matching (BGM) and 2D - Gabor filter techniques. Then, a State Vector Machine (SVM), Weighted Euclidian Distance (WED) and Jaccard coefficient and Dice coefficient classifier is used to verify and authenticate the patterns. Accordingly, SVM is regarded as most distinctive and most efficient technique for the proposed iris identification and authentication system.