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A Feature Level Extraction based on Iris Recognition for Secure Biometric Authentication

by Gourav Sachdeva, Bikrampal Kaur
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 123 - Number 11
Year of Publication: 2015
Authors: Gourav Sachdeva, Bikrampal Kaur
10.5120/ijca2015905586

Gourav Sachdeva, Bikrampal Kaur . A Feature Level Extraction based on Iris Recognition for Secure Biometric Authentication. International Journal of Computer Applications. 123, 11 ( August 2015), 13-17. DOI=10.5120/ijca2015905586

@article{ 10.5120/ijca2015905586,
author = { Gourav Sachdeva, Bikrampal Kaur },
title = { A Feature Level Extraction based on Iris Recognition for Secure Biometric Authentication },
journal = { International Journal of Computer Applications },
issue_date = { August 2015 },
volume = { 123 },
number = { 11 },
month = { August },
year = { 2015 },
issn = { 0975-8887 },
pages = { 13-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume123/number11/22002-2015905586/ },
doi = { 10.5120/ijca2015905586 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:12:25.574843+05:30
%A Gourav Sachdeva
%A Bikrampal Kaur
%T A Feature Level Extraction based on Iris Recognition for Secure Biometric Authentication
%J International Journal of Computer Applications
%@ 0975-8887
%V 123
%N 11
%P 13-17
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Iris recognition is most precise and consistent biometric identification system accessible in the current situation. The demand for an accurate biometric system that provides dependable identification and verification of an individual has increased over the years. A biometric system that provides reliable and accurate identification of an individual is an iris recognition system. This reliability is provided by unique patterns of human iris which differs from person to person up to an extent of identical twins having different iris patterns. This paper has proposed the hybridization of Hough Circular Transform, Scale Invariant Feature Transform and Genetic Algorithm. The genetic algorithm is applied to optimize the features set as obtained by Scale invariant feature transform.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Iris Recognition Hough Transformation SIFT Genetic Algorithm.

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