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Reseach Article

Article:Iris Recognition System with Accurate Eyelash Segmentation & Improved FAR, FRR using Textural & Topological Features

by Archana V Mire, Bharti L Dhote
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 7 - Number 9
Year of Publication: 2010
Authors: Archana V Mire, Bharti L Dhote
10.5120/1281-1652

Archana V Mire, Bharti L Dhote . Article:Iris Recognition System with Accurate Eyelash Segmentation & Improved FAR, FRR using Textural & Topological Features. International Journal of Computer Applications. 7, 9 ( October 2010), 1-5. DOI=10.5120/1281-1652

@article{ 10.5120/1281-1652,
author = { Archana V Mire, Bharti L Dhote },
title = { Article:Iris Recognition System with Accurate Eyelash Segmentation & Improved FAR, FRR using Textural & Topological Features },
journal = { International Journal of Computer Applications },
issue_date = { October 2010 },
volume = { 7 },
number = { 9 },
month = { October },
year = { 2010 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume7/number9/1281-1652/ },
doi = { 10.5120/1281-1652 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:55:49.834802+05:30
%A Archana V Mire
%A Bharti L Dhote
%T Article:Iris Recognition System with Accurate Eyelash Segmentation & Improved FAR, FRR using Textural & Topological Features
%J International Journal of Computer Applications
%@ 0975-8887
%V 7
%N 9
%P 1-5
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper represents novel iris recognition technique which uses textural and topological features. Converting circular iris pattern into rectangular pattern makes it rotation invariant. Most of the research in iris recognition is on encoding and recognition of iris pattern but segmenting exact iris pattern is itself very tedious task in this paper we are trying to emphasize on better iris segmentation technique . In other systems performance of the system is always dependent on threshold. There is always conflict between FAR & FRR, if tied to improve one quantity degrades other one. This paper describes an alternate means to identify individuals using images of their iris with low false acceptance rate and low false rejection rate. For encoding topological feature Euler vector can be utilized while for encoding textural feature histogram is used. Histogram is matched by using Du measure whose origin belong in Hyperspectral Image Analysis while for matching euler vector Vector Difference Matching algorithm is developed .

References
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  3. Arijit Bishnu, Bhargab B. Bhattacharya y, Malay K. Kundu, C. A. Murthy “Euler Vector: A Combinatorial Signature for Gray-Tone Images “ Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC.02)
  4. “The CASIA iris image database,” Available at http://www.sinobiometrics.com.
  5. R BREMANANTH and A CHITRA “New methodology for a person identification system” Sadhana Vol. 31, Part 3, June 2006, pp. 259–276.
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  7. Y. Du, C.-I. Chang, H. Ren, F.M. D'Amico, J. Jensen, J., "A New Hyperspectral Discrimination Measure for Spectral Similarity", Optical Engineering, Vol. 43, No. 8, 2004.
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Index Terms

Computer Science
Information Sciences

Keywords

Histogram Du measure Euler vector FAR FRR