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Detection and Localization of Iris Features for Person Identification using Digital Image Processing Techniques and Pattern Recognition Approach

by Ashwini Chate, Pramod Kumar, Sushilkumar Holambe
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 24
Year of Publication: 2021
Authors: Ashwini Chate, Pramod Kumar, Sushilkumar Holambe
10.5120/ijca2021921605

Ashwini Chate, Pramod Kumar, Sushilkumar Holambe . Detection and Localization of Iris Features for Person Identification using Digital Image Processing Techniques and Pattern Recognition Approach. International Journal of Computer Applications. 183, 24 ( Sep 2021), 9-15. DOI=10.5120/ijca2021921605

@article{ 10.5120/ijca2021921605,
author = { Ashwini Chate, Pramod Kumar, Sushilkumar Holambe },
title = { Detection and Localization of Iris Features for Person Identification using Digital Image Processing Techniques and Pattern Recognition Approach },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2021 },
volume = { 183 },
number = { 24 },
month = { Sep },
year = { 2021 },
issn = { 0975-8887 },
pages = { 9-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume183/number24/32073-2021921605/ },
doi = { 10.5120/ijca2021921605 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:17:44.727388+05:30
%A Ashwini Chate
%A Pramod Kumar
%A Sushilkumar Holambe
%T Detection and Localization of Iris Features for Person Identification using Digital Image Processing Techniques and Pattern Recognition Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 24
%P 9-15
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Biometrics Systems are computerized methods for verification or recognition to the identity of a living person on the basis of some physiological characteristics. Human eyes are completely unique and can be used for biometric purposes. In the proposed research work, extraction of iris is done by using digital image processing techniques. For experimentation and implementation, a dataset of IIT Delhi, UBIRIS and UPOL iris image database has been used and the evaluation results clearly demonstrate that the proposed iris segmentation technique provides better accuracy in iris recognition rather than existing techniques. Classification is done by using supervised and unsupervised pattern classification techniques. Support vector machine and k-means clustering is used for classification iris features. Overall got 97.25% accuracy based on confusion matrix. The results clearly prove that the proposed technique provides better, rather than existing techniques.

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Index Terms

Computer Science
Information Sciences

Keywords

Iris Detection Digital Image Processing Pattern Classification Supervised Learning Unsupervised Learning.