Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 38, Issue 9, Pages 11105-11111Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2011.02.155
Keywords
Feature selection; Information fusion; Multimodal biometric; Face recognition; Iris recognition; Support vector machine
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Multimodal biometric can overcome the limitation possessed by single biometric trait and give better classification accuracy. This paper proposes face-iris multimodal biometric system based on fusion at matching score level using support vector machine (SVM). The performances of face and iris recognition can be enhanced using a proposed feature selection method to select an optimal subset of features. Besides, a simple computation speed-up method is proposed for SVM. The results show that the proposed feature selection method is able improve the classification accuracy in terms of total error rate. The support vector machine-based fusion method also gave very promising results. (C) 2011 Elsevier Ltd. All rights reserved.
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