A face and speech biometric verification system using a simple Bayesian structure

Identity verification systems that use a mono modal biometric always have to contend with sensor noise and limitations of the feature extractor and matcher, while combining information from different biometrics modalities may well provide higher and more consistent performance levels, However, an in...

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Main Authors: Teoh, , ABJ, Samad, , SA, Hussain,, A
Format: Article
Published: 2005
Subjects:
Online Access:http://shdl.mmu.edu.my/2173/
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author Teoh, , ABJ
Samad, , SA
Hussain,, A
author_facet Teoh, , ABJ
Samad, , SA
Hussain,, A
author_sort Teoh, , ABJ
building MMU Institutional Repository
collection Online Access
description Identity verification systems that use a mono modal biometric always have to contend with sensor noise and limitations of the feature extractor and matcher, while combining information from different biometrics modalities may well provide higher and more consistent performance levels, However, an intelligent scheme is required to fuse the decisions produced by the individual sensors. This paper presents a decision fusion technique for a bimodal biometric verification system that makes use of facial and speech biometrics. The decision fusion schemes considered have simple Bayesian structures (SBS) that particularize the univariat Gaussian density function, Beta density function or Parzen window density estimation. SBS has advantages in terms Of Computation speed, storage space and its open framework. The performances of SBS is evaluated and compared with that of other classical classification approaches, such as sum rule and Multilayer Perceptron, on a bimodal database.
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spelling mmu-21732011-09-19T08:21:03Z http://shdl.mmu.edu.my/2173/ A face and speech biometric verification system using a simple Bayesian structure Teoh, , ABJ Samad, , SA Hussain,, A QA75.5-76.95 Electronic computers. Computer science Identity verification systems that use a mono modal biometric always have to contend with sensor noise and limitations of the feature extractor and matcher, while combining information from different biometrics modalities may well provide higher and more consistent performance levels, However, an intelligent scheme is required to fuse the decisions produced by the individual sensors. This paper presents a decision fusion technique for a bimodal biometric verification system that makes use of facial and speech biometrics. The decision fusion schemes considered have simple Bayesian structures (SBS) that particularize the univariat Gaussian density function, Beta density function or Parzen window density estimation. SBS has advantages in terms Of Computation speed, storage space and its open framework. The performances of SBS is evaluated and compared with that of other classical classification approaches, such as sum rule and Multilayer Perceptron, on a bimodal database. 2005-11 Article NonPeerReviewed Teoh, , ABJ and Samad, , SA and Hussain,, A (2005) A face and speech biometric verification system using a simple Bayesian structure. JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 21 (6). pp. 1121-1137. ISSN 1016-2364
spellingShingle QA75.5-76.95 Electronic computers. Computer science
Teoh, , ABJ
Samad, , SA
Hussain,, A
A face and speech biometric verification system using a simple Bayesian structure
title A face and speech biometric verification system using a simple Bayesian structure
title_full A face and speech biometric verification system using a simple Bayesian structure
title_fullStr A face and speech biometric verification system using a simple Bayesian structure
title_full_unstemmed A face and speech biometric verification system using a simple Bayesian structure
title_short A face and speech biometric verification system using a simple Bayesian structure
title_sort face and speech biometric verification system using a simple bayesian structure
topic QA75.5-76.95 Electronic computers. Computer science
url http://shdl.mmu.edu.my/2173/