An Improved Score Level Fusion in Multimodal Biometric Systems

Authors:
Shi-Jinn Horng;Yuan-Hsin Chen;Ray-Shine Run;Rong-Jian Chen;Jui-Lin Lai;Kevin Octavius Sentosal
Affiliations:
-;-;-;-;-;-
Venue:
PDCAT '09 Proceedings of the 2009 International Conference on Parallel and Distributed Computing, Applications and Technologies
Year:
2009

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Abstract

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.