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

来源：

2009 INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED COMPUTING, APPLICATIONS AND TECHNOLOGIES (PDCAT 2009) | 2009年

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

页码：239 / +

页数：3

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