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Multimodal Classification using Feature Level Fusion and SVM

by Priyanka Sharma, Manavjeet Kaur
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 76 - Number 4
Year of Publication: 2013
Authors: Priyanka Sharma, Manavjeet Kaur
10.5120/13236-0670

Priyanka Sharma, Manavjeet Kaur . Multimodal Classification using Feature Level Fusion and SVM. International Journal of Computer Applications. 76, 4 ( August 2013), 26-32. DOI=10.5120/13236-0670

@article{ 10.5120/13236-0670,
author = { Priyanka Sharma, Manavjeet Kaur },
title = { Multimodal Classification using Feature Level Fusion and SVM },
journal = { International Journal of Computer Applications },
issue_date = { August 2013 },
volume = { 76 },
number = { 4 },
month = { August },
year = { 2013 },
issn = { 0975-8887 },
pages = { 26-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume76/number4/13236-0670/ },
doi = { 10.5120/13236-0670 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:45:02.389614+05:30
%A Priyanka Sharma
%A Manavjeet Kaur
%T Multimodal Classification using Feature Level Fusion and SVM
%J International Journal of Computer Applications
%@ 0975-8887
%V 76
%N 4
%P 26-32
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The use of biometrics in the field of enhancing security and authentication in sensitive systems is a rapidly evolving technology. The increasing attacks and decreasing security in unimodal systems have resulted in designing multimodal systems combining different biometric traits. A lot of research has already been done in designing multimodal systems with fusion at rank and match-score level using different classifiers such as Bayesian classifiers, LDA, ANNs and SVMs. In this research work, a multimodal system is designed by integrating face, fingerprint and palmprint based on feature level fusion. Each of the feature vectors are extracted independently using PCA and then fused together to perform classification using a multiclass SVM. The classification is performed on a set of test images taken from both the standard databases and live images captured in biometric lab.

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Index Terms

Computer Science
Information Sciences

Keywords

Multimodal biometric system Feature level fusion PCA SVM

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