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Reseach Article

Iris Segmentation using Geodesic Active Contour for Improved Texture Extraction in Recognition

by Minal K. Pawar, Sunita S. Lokhande, V. N. Bapat
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 47 - Number 16
Year of Publication: 2012
Authors: Minal K. Pawar, Sunita S. Lokhande, V. N. Bapat

Minal K. Pawar, Sunita S. Lokhande, V. N. Bapat . Iris Segmentation using Geodesic Active Contour for Improved Texture Extraction in Recognition. International Journal of Computer Applications. 47, 16 ( June 2012), 40-47. DOI=10.5120/7276-0486

@article{ 10.5120/7276-0486,
author = { Minal K. Pawar, Sunita S. Lokhande, V. N. Bapat },
title = { Iris Segmentation using Geodesic Active Contour for Improved Texture Extraction in Recognition },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 47 },
number = { 16 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 40-47 },
numpages = {9},
url = { },
doi = { 10.5120/7276-0486 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T20:42:03.673629+05:30
%A Minal K. Pawar
%A Sunita S. Lokhande
%A V. N. Bapat
%T Iris Segmentation using Geodesic Active Contour for Improved Texture Extraction in Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 47
%N 16
%P 40-47
%D 2012
%I Foundation of Computer Science (FCS), NY, USA

Automatic identification/verification of a person through biometrics has been getting extensive attention due to an increasing importance of security. The most popular biometric authentication scheme employed for the last few years is Iris Recognition. The performance of iris recognition system highly depends on segmentation. For instance, even an effective feature extraction method would not be able to obtain useful information from an iris image that is not segmented accurately. The iris proposed recognition module consists of the preprocessing system, segmentation, feature extraction and recognition. Mainly it focuses on image segmentation using Geodesic Active Contours and comparison with traditional methods of segmentation. As active contours can 1) assume any shape and 2) segment multiple objects at the same time, they lessen some of the concerns related with conventional iris segmentation models. The iris texture is extracted in an iterative fashion by considering both local and global properties of the image. The matching accuracy of an iris recognition system is observed to improve upon application of the proposed segmentation algorithm. Experimental results on the CASIA (Institute of Automation, Chinese Academy of Sciences) Interval version3 iris databases implemented in MATLAB shows the efficiency of the proposed technique application.

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Index Terms

Computer Science
Information Sciences


Iris Recognition Iris Segmentation Level Sets Snakes Geodesic Active Contours (gacs) Iriscodes