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Multimodal Biometrics for Person Authentication using Hand Image

by S. Sumathi, R. Rani Hema Malini
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 70 - Number 24
Year of Publication: 2013
Authors: S. Sumathi, R. Rani Hema Malini
10.5120/12218-8400

S. Sumathi, R. Rani Hema Malini . Multimodal Biometrics for Person Authentication using Hand Image. International Journal of Computer Applications. 70, 24 ( May 2013), 43-48. DOI=10.5120/12218-8400

@article{ 10.5120/12218-8400,
author = { S. Sumathi, R. Rani Hema Malini },
title = { Multimodal Biometrics for Person Authentication using Hand Image },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 70 },
number = { 24 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 43-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume70/number24/12218-8400/ },
doi = { 10.5120/12218-8400 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:33:45.251608+05:30
%A S. Sumathi
%A R. Rani Hema Malini
%T Multimodal Biometrics for Person Authentication using Hand Image
%J International Journal of Computer Applications
%@ 0975-8887
%V 70
%N 24
%P 43-48
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

To obtain secure and accurate authentication system using most accepted biometrics Hand geometry in multimodal approach. Implement multi modal person authentication system using single input image with efficient features. In this proposed method Hand geometry and selected window size palm print features computed from same image is used for authentication. Integrating the features increases robustness of the system. Discrete Wavelet Transform (DWT) is used for feature extraction and Support Vector Machine (SVM) is proposed for classification. The final decision is made by fusion at matching score level. Experiments are carried out on the publicly available GPDS Hand Database. The achieved experimental results GAR=99. 47%, FAR=0% showed the effectiveness of system considered for high security applications.

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Index Terms

Computer Science
Information Sciences

Keywords

Hand geometry palm print multi modal biometrics DWT SVM Score level fusion

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