Development of Novel Feature For Iris Biometrics

Abstract

IRIS is one of the supreme biometric trait available, whose accuracy surprises everyone, better then DNA. There are numbered of algorithms proposed for the efficient result but fails due to limitations. All traditional iris recognition systems are not meant especially for iris image. They are being derived from other trades hoping that it will work with iris also. The mainly known feature in iris biometric is J Daugman’s Gabor filter. He has used Wavelet equation an applied Integro-differentiation operator to obtain Gabor filter. In this thesis, we have proposed a new scheme in feature detection, particularly for iris Biometric. We have taken Wavelet as a base equation and apply complex-exponential in the presence of Gaussian envelop. Our approach starts with the efficient sector based normalization and noise removal techniques, in the pre-processing phase of iris biometric. Then Creating feature keypixel from that normalised image. The enhancement of the keypixel is done to increase accuracy rate.