An Improved Score Level Fusion in Multimodal Biometric Systems

被引:15
|
作者
Horng, Shi-Jinn [1 ]
Chen, Yuan-Hsin [2 ]
Run, Ray-Shine [2 ]
Chen, Rong-Jian [2 ]
Lai, Jui-Lin [2 ]
Sentosal, Kevin Octavius [1 ]
机构
[1] Natl Taiwan Univ Sci & Technol, Dept Comp Sci & Informat Engn, Taipei 106, Taiwan
[2] Natl United Univ, Dept Elect Engn, Miaoli 36003, Taiwan
关键词
component; Multimodal biometrics; score level fusion; verification; normalization; sum rule;
D O I
10.1109/PDCAT.2009.82
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:239 / +
页数:3
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