Abstract
This paper presents an efficient Iris recognition system based on Fast Fourier Transform. The system is comprised of several algorithms which are employed to provide effective identification of an individual based on the individual's Iris pattern. The proposed combines canny edge detector and circular Hough transform model algorithms which yield more rapid and accurate Iris boundaries localization. The eyelid and eyelashes occlusion is also dealt with by applying non maxima radial suppression technique. The segmented Iris area is then normalized with all iris templates converted from circular to rectangular shape of standard dimensions thus enabling comparison between them. Fast Fourier Transform function is then applied to normalized Iris image. The resulting matrix consists of real and imaginary part represented by complex numbers. The matrix is encoded by assigning a sequence of binary numbers to each possible combination of complex numbers thus producing Iris code. In the matching phase the degree of dissimilarity between the two Iris codes is determined. The experimental results show that the obtained high recognition accuracy is competitive with other existing methods.
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