Iris feature extraction and recognition using Wavelet Packet Analysis

An iris recognition system based on Wavelet Packet Analysis is described. The most unique phenotypic feature visible in a person's face is the detailed texture of each eye's iris. The visible texture of a person's iris is encoded into a compact sequence of 2-D wavelet packet coefficients, which generate an “iris code”. Two different iris codes are compared using exclusively OR comparisons. In this paper, we propose a novel multi-resolution approach based on Wavelet Packet Transform (WPT) for iris texture analysis and recognition. The development of this approach is motivated by the observation that dominant frequencies of iris texture are located in the low and middle frequency channels. With an adaptive threshold, WPT sub images coefficients are quantized into 1, 0 as iris signature. This signature presents the local information of different irises. By using wavelet packets the size of the iris signature of code attained is 1280 bits. The signature of the new iris pattern is compared against the stored pattern after computing the signature of new iris pattern. Identification is performed by computing the hamming distance.