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Score Level Fusion of Multimodal Biometrics based on Entropy Function

by Sheikh Moeen Ul Haque, Moin Uddin, Jyotsana Grover
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 142 - Number 9
Year of Publication: 2016
Authors: Sheikh Moeen Ul Haque, Moin Uddin, Jyotsana Grover
10.5120/ijca2016909912

Sheikh Moeen Ul Haque, Moin Uddin, Jyotsana Grover . Score Level Fusion of Multimodal Biometrics based on Entropy Function. International Journal of Computer Applications. 142, 9 ( May 2016), 28-33. DOI=10.5120/ijca2016909912

@article{ 10.5120/ijca2016909912,
author = { Sheikh Moeen Ul Haque, Moin Uddin, Jyotsana Grover },
title = { Score Level Fusion of Multimodal Biometrics based on Entropy Function },
journal = { International Journal of Computer Applications },
issue_date = { May 2016 },
volume = { 142 },
number = { 9 },
month = { May },
year = { 2016 },
issn = { 0975-8887 },
pages = { 28-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume142/number9/24926-2016909912/ },
doi = { 10.5120/ijca2016909912 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:44:50.174200+05:30
%A Sheikh Moeen Ul Haque
%A Moin Uddin
%A Jyotsana Grover
%T Score Level Fusion of Multimodal Biometrics based on Entropy Function
%J International Journal of Computer Applications
%@ 0975-8887
%V 142
%N 9
%P 28-33
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents the score level fusion of multimodal biometrics using Hanman-Anirban entropy function. Entropy function captures the uncertainty in the scores. The experimental results ascertain that Entropy based score level fusion outperforms over existing methods of score level fusion such as t-norms, sum and max. We have validated our claim on finger-knuckle-print (FKP) dataset consisting of left index, left middle, right index and right middle FKP. The features of FKPs are extracted using the Gabor Wavelet. The implementation is done using MATLAB and the performance of the proposed technique is evaluated using Receiver Operating characteristics (ROC) curve.  The proposed score level fusion approach achieves significant improvement in the performance over the individual FKP. We obtain Genuine acceptance rate of 99% with FAR of 0.001 %.

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Index Terms

Computer Science
Information Sciences

Keywords

Finger Knuckle Print Score Level Fusion t-norms Gabor Wavelet Entropy Function Biometric-Authentication.

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