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An Efficient Supervised Approach for Retinal Person Identification using Zernike Moments

by Shubhra Aich, G M Al Mamun
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 81 - Number 7
Year of Publication: 2013
Authors: Shubhra Aich, G M Al Mamun
10.5120/14028-2375

Shubhra Aich, G M Al Mamun . An Efficient Supervised Approach for Retinal Person Identification using Zernike Moments. International Journal of Computer Applications. 81, 7 ( November 2013), 38-45. DOI=10.5120/14028-2375

@article{ 10.5120/14028-2375,
author = { Shubhra Aich, G M Al Mamun },
title = { An Efficient Supervised Approach for Retinal Person Identification using Zernike Moments },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 81 },
number = { 7 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 38-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume81/number7/14028-2375/ },
doi = { 10.5120/14028-2375 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:55:30.435745+05:30
%A Shubhra Aich
%A G M Al Mamun
%T An Efficient Supervised Approach for Retinal Person Identification using Zernike Moments
%J International Journal of Computer Applications
%@ 0975-8887
%V 81
%N 7
%P 38-45
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Zernike moments map images using orthogonal basis functions. These moments have the advantages of rotation invariance, robustness and minimum information redundancy. In this paper, we focus on distinguishable pattern analysis of the retinal fundus images for person identification using Zernike moments. These moments are used to form 11-D feature vectors and k-nearest neighbor (kNN) classifier is used for person identification on publicly available DRIVE and STARE databases. This method outperforms all the existing methods with accuracy of 100% and 98. 64% on DRIVE and STARE databases respectively. Its smaller dimension of feature vector, simplicity and robustness make this method suitable for real-time retinal person identification scheme.

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Index Terms

Computer Science
Information Sciences

Keywords

Zernike moments rotation invariance retinal biometrics kNN classifier person identification.

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