FUSION DECISION FOR A BIMODAL BIOMETRIC VERIFICATION SYSTEM USING SUPPORT VECTOR MACHINE AND ITS VARIATIONS

FUSION DECISION FOR A BIMODAL BIOMETRIC VERIFICATION SYSTEM USING SUPPORT VECTOR MACHINE AND ITS VARIATIONS

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This paw presents fusion detection technique comparisons based on support vector machine and its variations for a bimodal biometric verification system that makes use of face images and speech utterances. The system is essentially constructed by a face expert, a speech expert and a fusion decision m...

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Main Authors: A. Teoh, S.A. Samad, A. Hussain
Format: Article
Language:English
Published: Universitas Gadjah Mada 2017-12-01
Series:ASEAN Journal on Science and Technology for Development
Online Access:http://www.ajstd.org/index.php/ajstd/article/view/326
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spelling doaj-04140c2eb95f404b9d8669a0610dcd222020-11-24T23:04:54ZengUniversitas Gadjah MadaASEAN Journal on Science and Technology for Development0217-54602224-90282017-12-0119111610.29037/ajstd.326321FUSION DECISION FOR A BIMODAL BIOMETRIC VERIFICATION SYSTEM USING SUPPORT VECTOR MACHINE AND ITS VARIATIONSA. Teoh0S.A. Samad1A. Hussain2Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan MalaysiaDepartment of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan MalaysiaDepartment of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan MalaysiaThis paw presents fusion detection technique comparisons based on support vector machine and its variations for a bimodal biometric verification system that makes use of face images and speech utterances. The system is essentially constructed by a face expert, a speech expert and a fusion decision module. Each individual expert has been optimized to operate in automatic mode and designed for security access application. Fusion decision schemes considered are linear, weighted Support Vector Machine (SVM) and linear SVM with quadratic transformation. The conditions tested include the balanced and unbalanced conditions between the two experts in order to obtain the optimum fusion module from  these techniques best suited to the target application.http://www.ajstd.org/index.php/ajstd/article/view/326
collection DOAJ
language English
format Article
sources DOAJ
author A. Teoh
S.A. Samad
A. Hussain
spellingShingle A. Teoh
S.A. Samad
A. Hussain
FUSION DECISION FOR A BIMODAL BIOMETRIC VERIFICATION SYSTEM USING SUPPORT VECTOR MACHINE AND ITS VARIATIONS
ASEAN Journal on Science and Technology for Development
author_facet A. Teoh
S.A. Samad
A. Hussain
author_sort A. Teoh
title FUSION DECISION FOR A BIMODAL BIOMETRIC VERIFICATION SYSTEM USING SUPPORT VECTOR MACHINE AND ITS VARIATIONS
title_short FUSION DECISION FOR A BIMODAL BIOMETRIC VERIFICATION SYSTEM USING SUPPORT VECTOR MACHINE AND ITS VARIATIONS
title_full FUSION DECISION FOR A BIMODAL BIOMETRIC VERIFICATION SYSTEM USING SUPPORT VECTOR MACHINE AND ITS VARIATIONS
title_fullStr FUSION DECISION FOR A BIMODAL BIOMETRIC VERIFICATION SYSTEM USING SUPPORT VECTOR MACHINE AND ITS VARIATIONS
title_full_unstemmed FUSION DECISION FOR A BIMODAL BIOMETRIC VERIFICATION SYSTEM USING SUPPORT VECTOR MACHINE AND ITS VARIATIONS
title_sort fusion decision for a bimodal biometric verification system using support vector machine and its variations
publisher Universitas Gadjah Mada
series ASEAN Journal on Science and Technology for Development
issn 0217-5460
2224-9028
publishDate 2017-12-01
description This paw presents fusion detection technique comparisons based on support vector machine and its variations for a bimodal biometric verification system that makes use of face images and speech utterances. The system is essentially constructed by a face expert, a speech expert and a fusion decision module. Each individual expert has been optimized to operate in automatic mode and designed for security access application. Fusion decision schemes considered are linear, weighted Support Vector Machine (SVM) and linear SVM with quadratic transformation. The conditions tested include the balanced and unbalanced conditions between the two experts in order to obtain the optimum fusion module from  these techniques best suited to the target application.
url http://www.ajstd.org/index.php/ajstd/article/view/326
work_keys_str_mv AT ateoh fusiondecisionforabimodalbiometricverificationsystemusingsupportvectormachineanditsvariations
AT sasamad fusiondecisionforabimodalbiometricverificationsystemusingsupportvectormachineanditsvariations
AT ahussain fusiondecisionforabimodalbiometricverificationsystemusingsupportvectormachineanditsvariations
_version_ 1725628707843866624

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