Iris Recognition Using Improved Xor-Sum Code

Bala, N. and Vyas, R. and Gupta, R. and Kumar, A. (2021) Iris Recognition Using Improved Xor-Sum Code. In: Security and Privacy : Select Proceedings of ICSP 2020. Lecture Notes in Electrical Engineering . Springer, Singapore, pp. 107-117. ISBN 9789813367807

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Abstract

Iris recognition has been among the most secure and reliable biometric traits, because of its permanent and unique features. Among the various essential modules of an iris recognition framework, feature extraction has been the most sought-for module, where numerous research works have been carried out to yield an effective representation of iris features. This paper is an attempt to propose an improved version of a famous feature descriptor, called Xor-sum code, to obtain an enhanced recognition accuracy. The proposed approach incorporates the curvature information into the conventional Gabor filter, to facilitate discriminative iris feature representation. A rigorous experimentation, with two challenging benchmark iris datasets, has been performed to approve the viability of suggested strategy. The approach proposed under this work is also generalized to work with both the near-infrared and visible wavelength images.