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Reseach Article

A Comprehensive Study of Palmprint based Authentication

by Madasu Hanmandlu, Neha Mittal, Ankit Gureja, Ritu Vijay
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 37 - Number 2
Year of Publication: 2012
Authors: Madasu Hanmandlu, Neha Mittal, Ankit Gureja, Ritu Vijay
10.5120/4580-6499

Madasu Hanmandlu, Neha Mittal, Ankit Gureja, Ritu Vijay . A Comprehensive Study of Palmprint based Authentication. International Journal of Computer Applications. 37, 2 ( January 2012), 17-24. DOI=10.5120/4580-6499

@article{ 10.5120/4580-6499,
author = { Madasu Hanmandlu, Neha Mittal, Ankit Gureja, Ritu Vijay },
title = { A Comprehensive Study of Palmprint based Authentication },
journal = { International Journal of Computer Applications },
issue_date = { January 2012 },
volume = { 37 },
number = { 2 },
month = { January },
year = { 2012 },
issn = { 0975-8887 },
pages = { 17-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume37/number2/4580-6499/ },
doi = { 10.5120/4580-6499 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:23:15.693246+05:30
%A Madasu Hanmandlu
%A Neha Mittal
%A Ankit Gureja
%A Ritu Vijay
%T A Comprehensive Study of Palmprint based Authentication
%J International Journal of Computer Applications
%@ 0975-8887
%V 37
%N 2
%P 17-24
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents some new features for the palmprint based authentication. The Region of interest (ROI) is extracted from the palmprint image by finding a tangent to the curves between fingers. The perpendicular bisector of this tangent and the tangent itself help demarcate the rectangular area that forms the ROI of the palmprint. Four approaches are presented for the feature extraction. In the first approach the ROI is divided into a suitable number of non-overlapping windows from which fuzzy features are extracted. In the second approach multi-scale wavelet decomposition is applied on the ROI and the detail images are combined to yield a composite image which is partitioned into non-overlapping windows and energy features are extracted. In the third approach sigmoid features are extracted from the ROI and in the fourth approach feature extraction is done using Local Binary Pattern (LBP) based on the directional gradient response. These four sets of features are used for the authentication of users from two databases using Euclidean Distance, Chi square measure and Support Vector Machines as classifiers.

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Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy features Wavelet features sigmoid feature Local Binary Pattern Support Vector Machines