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Comparative Analysis of Distinct Fusion Levels in Multimodal Biometrics

Published on September 2015 by Vinay Kumar.M. S, R. Srikantaswamy
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National Conference “Electronics, Signals, Communication and Optimization"
Foundation of Computer Science USA
NCESCO2015 - Number 4
September 2015
Authors: Vinay Kumar.M. S, R. Srikantaswamy
ad49e4ed-e2a4-4a95-95cd-c8fa02c0b779

Vinay Kumar.M. S, R. Srikantaswamy . Comparative Analysis of Distinct Fusion Levels in Multimodal Biometrics. National Conference “Electronics, Signals, Communication and Optimization". NCESCO2015, 4 (September 2015), 1-4.

@article{
author = { Vinay Kumar.M. S, R. Srikantaswamy },
title = { Comparative Analysis of Distinct Fusion Levels in Multimodal Biometrics },
journal = { National Conference “Electronics, Signals, Communication and Optimization" },
issue_date = { September 2015 },
volume = { NCESCO2015 },
number = { 4 },
month = { September },
year = { 2015 },
issn = 0975-8887,
pages = { 1-4 },
numpages = 4,
url = { /proceedings/ncesco2015/number4/22313-5333/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference “Electronics, Signals, Communication and Optimization"
%A Vinay Kumar.M. S
%A R. Srikantaswamy
%T Comparative Analysis of Distinct Fusion Levels in Multimodal Biometrics
%J National Conference “Electronics, Signals, Communication and Optimization"
%@ 0975-8887
%V NCESCO2015
%N 4
%P 1-4
%D 2015
%I International Journal of Computer Applications
Abstract

Nowadays, Multimodal biometrics has created a substantial interest in the field of identification management due to higher recognition performance. This paper presents a comparative analysis of different fusion levels like feature level, score level and decision level in multimodal biometrics using fingerprint and face. Histogram of Oriented Gradients (HOG) descriptor has been used for fingerprint recognition, Linear Discriminant analysis (LDA) along with Principal component analysis (PCA) for feature reduction and face recognition. These modalities are combined at different fusion levels and the results have shown that biometric fusion at feature level gives superior performance when compared to score level and decision level.

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Index Terms

Computer Science
Information Sciences

Keywords

Multimodal Biometrics Feature Level Score Level Decision Level.