Biometric personal identification based on iris pattern recognition using Wavelet Packet Transform

A new iris recognition system based on Wavelet Packet Analysis and Morlet wavelet is described. Morlet wavelet calculations are easy compared to Gabor wavelets. Moreover Gabor wavelet based iris recognition system is patented which blocks its further development. 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 Morlet wavelet coefficients, which generate an “iris code” of 4096-bits. 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 or −1 as iris signature. This signature presents the local information of different irises. The signature of the new iris pattern is compared against the stored pattern after computing the signature of new iris pattern and identification is performed