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2009 International Conference on Parallel and Distributed Computing, Applications and Technologies
An Improved Score Level Fusion in Multimodal Biometric Systems
Higashi Hiroshima, Japan
December 08-December 11
ISBN: 978-0-7695-3914-0
ASCII Text
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Shi-Jinn Horng, Yuan-Hsin Chen, Ray-Shine Run, Rong-Jian Chen, Jui-Lin Lai, Kevin Octavius Sentosal, "An Improved Score Level Fusion in Multimodal Biometric Systems," Parallel and Distributed Computing Applications and Technologies, International Conference on, pp. 239-246, 2009 International Conference on Parallel and Distributed Computing, Applications and Technologies, 2009.
 
 
BibTex
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@article{ 10.1109/PDCAT.2009.82,
author = {Shi-Jinn Horng and Yuan-Hsin Chen and Ray-Shine Run and Rong-Jian Chen and Jui-Lin Lai and Kevin Octavius Sentosal},
title = {An Improved Score Level Fusion in Multimodal Biometric Systems},
journal ={Parallel and Distributed Computing Applications and Technologies, International Conference on},
volume = {0},
year = {2009},
isbn = {978-0-7695-3914-0},
pages = {239-246},
doi = {http://doi.ieeecomputersociety.org/10.1109/PDCAT.2009.82},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Parallel and Distributed Computing Applications and Technologies, International Conference on
TI - An Improved Score Level Fusion in Multimodal Biometric Systems
SN - 978-0-7695-3914-0
SP239
EP246
A1 - Shi-Jinn Horng,
A1 - Yuan-Hsin Chen,
A1 - Ray-Shine Run,
A1 - Rong-Jian Chen,
A1 - Jui-Lin Lai,
A1 - Kevin Octavius Sentosal,
PY - 2009
KW - Multimodal biometrics
KW - score level fusion
KW - verification
KW - normalization
KW - sum rule
VL - 0
JA - Parallel and Distributed Computing Applications and Technologies, International Conference on
ER -
 
In a multimodal biometric system, the effective fusion method is necessary for combining information from various single modality systems. In this paper we examined the performance of sum rule-based score level fusion and Support Vector Machines (SVM)-based score level fusion. Three biometric characteristics were considered in this study: fingerprint, face, and finger vein. We also proposed a new robust normalization scheme (Reduction of High-scores Effect normalization) which is derived from min-max normalization scheme. Experiments on four different multimodal databases suggest that integrating the proposed scheme in sum rule-based fusion and SVM-based fusion leads to consistently high accuracy.
Index Terms:
Multimodal biometrics, score level fusion, verification, normalization, sum rule
Citation:
Shi-Jinn Horng, Yuan-Hsin Chen, Ray-Shine Run, Rong-Jian Chen, Jui-Lin Lai, Kevin Octavius Sentosal, "An Improved Score Level Fusion in Multimodal Biometric Systems," pdcat, pp.239-246, 2009 International Conference on Parallel and Distributed Computing, Applications and Technologies, 2009
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