DUAL FEATURE EXTRACTION TECHNIQUES FOR IRIS RECOGNITION SYSTEM

Abstract

The extraction of feature remains the significant phase in recognition system using iris. A successful recognition rate and reduction in classification time of two iris templates mostly depend on efficient feature extraction technique. This paper performs comparative analysis on two selected feature extraction techniques: Gabor Wavelet Transform (GWT) and Scale Invariant Feature Transform (SIFT). The developed system was evaluated with CASIA iris dataset. Performance evaluation of the system based on False Acceptance Rate (FAR), False Rejection Rate (FRR), Error Rate (ER) and accuracy produced different results of each technique. It was showed that the Gabor Wavelet Transform gave FAR of 0.9500, FRR of 0.0750, 92% of accuracy, and ER of 8% as compared with the SIFT technique which gave FAR of 0.900, FRR of 0.0631, ERR of 16.6% and 88.33% of accuracy. Finally, the results of comparative analysis showed that Gabor Wavelet Transform outperformed SIFT technique. From the results obtained, GWT is strongly recommended as a feature extraction method for the development of a robust iris authentication system.