A Novel Method to Extract Features for Iris Recognition System

In general, the iris recognition systems have used the wavelet transform as feature extraction techniques. Since the wavelet transform does not have the shift-invariant property, the iris features are inconsistently extracted due to the eye image rotation and the inexact iris localization. In this paper, a novel method to extract features is proposed for iris recognition system. Two types of features are obtained from the discrete wavelet frame decomposition. The first one is the global feature which is insensitive to the iris image deformation. The second one is the local feature which can represent the iris local texture. If the global distance between the test image and the stored one in the database is smaller than the threshold value, it is added to the candidates. And then, local matching is performed by Hamming distance. Experimental results show the proposed system could be used for the personal recognition efficiently.