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Illumination Invariant Feature Extraction for Multispectral Palmprint Verification

by Venkateswaran N., Saranraj S., Sudharsan S.
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International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 11 - Number 3
Year of Publication: 2016
Authors: Venkateswaran N., Saranraj S., Sudharsan S.
10.5120/ijais2016451586

Venkateswaran N., Saranraj S., Sudharsan S. . Illumination Invariant Feature Extraction for Multispectral Palmprint Verification. International Journal of Applied Information Systems. 11, 3 ( Aug 2016), 11-20. DOI=10.5120/ijais2016451586

@article{ 10.5120/ijais2016451586,
author = { Venkateswaran N., Saranraj S., Sudharsan S. },
title = { Illumination Invariant Feature Extraction for Multispectral Palmprint Verification },
journal = { International Journal of Applied Information Systems },
issue_date = { Aug 2016 },
volume = { 11 },
number = { 3 },
month = { Aug },
year = { 2016 },
issn = { 2249-0868 },
pages = { 11-20 },
numpages = {9},
url = { https://www.ijais.org/archives/volume11/number3/925-2016451586/ },
doi = { 10.5120/ijais2016451586 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T19:03:54.697428+05:30
%A Venkateswaran N.
%A Saranraj S.
%A Sudharsan S.
%T Illumination Invariant Feature Extraction for Multispectral Palmprint Verification
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 11
%N 3
%P 11-20
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The aim of biometrics is to identify humans from their personal traits more efficiently using devices, algorithms and procedures for applications that require security and authentication. Multispectral image analysis has gained importance due to its potential for accurate and faster recognition performance.  In this paper, Multispectral palmprint biometric system is proposed which uses the fusion of both MS and visible image to acquire more discriminative palm print information. The proposed system collects palm print images in visible and NIR bands. PCA based Fusion algorithm has been used to obtain more informative palmprint. First, Region of Interest (ROI) is extracted from the acquired palm print images. Then, features are extracted using phase congruency, histogram of gradient, Gabor filter and adaptive thresholding based algorithms. Simple distortion based measures are used for recognition. The proposed system is tested on a palmprint data collected using 080GE multispectral camera. Simulation results show high recognition performance using Gabor features obtained by fusion of visible and NIR palm print image.

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Index Terms

Computer Science
Information Sciences

Keywords

Biometrics Multispectral image Region of interest (ROI) Phase Congruency HoG Adaptive thresholding Gabor filter

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