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Reseach Article

An Adaptive Multimodal Biometric Recognition Algorithm for Face Image using Speech Signal

by M. Nageshkumar, M.N. ShanmukhaSwamy
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 7 - Number 1
Year of Publication: 2010
Authors: M. Nageshkumar, M.N. ShanmukhaSwamy
10.5120/1132-1483

M. Nageshkumar, M.N. ShanmukhaSwamy . An Adaptive Multimodal Biometric Recognition Algorithm for Face Image using Speech Signal. International Journal of Computer Applications. 7, 1 ( September 2010), 12-18. DOI=10.5120/1132-1483

@article{ 10.5120/1132-1483,
author = { M. Nageshkumar, M.N. ShanmukhaSwamy },
title = { An Adaptive Multimodal Biometric Recognition Algorithm for Face Image using Speech Signal },
journal = { International Journal of Computer Applications },
issue_date = { September 2010 },
volume = { 7 },
number = { 1 },
month = { September },
year = { 2010 },
issn = { 0975-8887 },
pages = { 12-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume7/number1/1132-1483/ },
doi = { 10.5120/1132-1483 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:55:18.686133+05:30
%A M. Nageshkumar
%A M.N. ShanmukhaSwamy
%T An Adaptive Multimodal Biometric Recognition Algorithm for Face Image using Speech Signal
%J International Journal of Computer Applications
%@ 0975-8887
%V 7
%N 1
%P 12-18
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A multimodal biometric authentication system based on plastic surgery face image using text dependent speech signal is described in this paper. In addition, the system is designed to keep the rate as high as possible for the plastic surgery face image by using text dependent speech signal. Each module of the system, i.e. the face and speech, is developed separately and fusion is done at matching level to obtain the optimal score for the multimodal biometric recognition system. Although information fusion in a multimodal system can be performed at various levels, integration at the matching score level is the most common approach due to the ease in accessing and combining the scores generated by different matchers. Since the matching scores output by the various modalities are heterogeneous, score normalization is needed to transform these scores into a common domain, prior to combining them.

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Index Terms

Computer Science
Information Sciences

Keywords

Multimodal biometric system Plastic surgery face image Speech signal Matching Score level Fusion