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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
computer science
Performance evaluation of score level fusion in multimodal biometric systems
Pattern Recognition, Volume 43, No. 5, Year 2010
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Description
In a multimodal biometric system, the effective fusion method is necessary for combining information from various single modality systems. In this paper the performance of sum rule-based score level fusion and support vector machines (SVM)-based score level fusion are examined. Three biometric characteristics are 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. The performance of simple sum rule-based fusion preceded by our normalization scheme is comparable to another approach, likelihood ratio-based fusion [8] (Nandakumar et al., 2008), which is based on the estimation of matching scores densities. Comparison between experimental results on sum rule-based fusion and SVM-based fusion reveals that the latter could attain better performance than the former, provided that the kernel and its parameters have been carefully selected. © 2009 Elsevier Ltd. All rights reserved.
Authors & Co-Authors
He, Mingxing
China, Chengdu
Xihua University
Horng, Shi Jinn
China, Chengdu
Xihua University
Taiwan, Taipei
National Taiwan University of Science and Technology
China, Chengdu
Southwest Jiaotong University
United States, Atlanta
Georgia State University
Fan, Pingzhi
China, Chengdu
Southwest Jiaotong University
Run, Ray Shine
Taiwan, Miao-li
National United University Taiwan
Chen, Rongjian
Taiwan, Miao-li
National United University Taiwan
Lai, Juilin
Taiwan, Miao-li
National United University Taiwan
Khan, Muhammad Khurram
Saudi Arabia, Riyadh
King Saud University
Sentosa, Kevin Octavius
Taiwan, Taipei
National Taiwan University of Science and Technology
Statistics
Citations: 252
Authors: 8
Affiliations: 6
Identifiers
Doi:
10.1016/j.patcog.2009.11.018
ISSN:
00313203
Study Design
Case-Control Study