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General Information
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2014 Vol.6(5): 416-420 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2014.V6.901

Iris Recognition Using Level Set and Local Binary Pattern

Brian O’Connor and Kaushik Roy
Abstract—This paper presents an efficient algorithm for iris recognition using the Level Set (LS) method and Local Binary Pattern (LBP). We deploy a Distance Regularized Level Set (DRLS)-based iris segmentation procedure in which the regularity of the Level Set (LS) function is intrinsically maintained during the curve propagation process. The LS evolution is derived as the gradient flow that minimizes energy functional with a distance regularization term and an external energy that drives the motion of the zero LS toward iris boundary accurately. DRLS also uses relatively large time steps in the finite difference scheme to reduce the curve propagation time. The deployed variational model is robust against poor localization and weak iris/sclera boundaries. Furthermore, we apply a Modified LBP (MLBP) in an effort to elicit the iris feature elements. The MLBP combines both the sign and magnitude features for the improvement of iris texture classification performance. The identification and verification performance of the proposed scheme is validated using the CASIA version 3 interval dataset.

Index Terms—Iris recognition, distance regularized level set, modified local binary pattern.

The authors are with the Computer Science Department, North Carolina Agricultural and Technical State University, Greensboro, NC 27411 USA (e-mail: bpoconno@aggies.ncat.edu, kroy@ncat.edu).


Cite:Brian O’Connor and Kaushik Roy, "Iris Recognition Using Level Set and Local Binary Pattern," International Journal of Computer Theory and Engineering vol. 6, no. 5, pp. 416-420, 2014.

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