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Iris Recognition Using Improved Xor-Sum Code

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Publication date2/04/2021
Host publicationSecurity and Privacy: Select Proceedings of ICSP 2020
EditorsPantelimon Stănică, Sugata Gangopadhyay, Sumit Kumar Debnath
Place of PublicationSingapore
Number of pages11
ISBN (electronic)9879813367814
ISBN (print)9789813367807 , 9789813367838
<mark>Original language</mark>English

Publication series

NameLecture Notes in Electrical Engineering
ISSN (Print)1876-1100
ISSN (electronic)1876-1119


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.