Iris recognition using stable dark features
Date of Issue2013
School of Computer Engineering
Centre for High Performance Embedded Systems
We propose a novel approach for iris recognition in less constrained environments that takes into account imaging noise arising from image capture outside the Depth of Field (DOF) of cameras. The proposed approach utilizes stable dark regions in iris images for recognition and does not rely on special hardware or on computationally expensive image restoration algorithms. We have employed a Gabor-based model to establish that stable features, which are not sensitive to defocus, correspond to local regions in iris images with low gray-level intensity. We will also present an approach to identify stable bits from the iris code representation, which correspond to dark regions in the enrolled image. Only these stable bits are used for recognition. Experimental results based on 15,000 images with varying degree of defocus show that the proposed method achieves an average recognition performance gain of about 1.45 times over a conventional method that relies on the entire code representation for iris recognition.
DRNTU::Engineering::Computer science and engineering::Computer applications
Journal of computers
© 2013 Academy Publisher. This paper was published in Journal of Computers and is made available as an electronic reprint (preprint) with permission of Academy Publisher. The paper can be found at the following official DOI: [http://dx.doi.org/10.4304/jcp.8.1.41-48]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.