Designing efficient fusion schemes for multimodal biometric systems using face and palmprint |
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Authors: | R Raghavendra [Author Vitae] Bernadette Dorizzi [Author Vitae] [Author Vitae] G Hemantha Kumar [Author Vitae] |
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Affiliation: | a Department of Studies in Computer Science, University of Mysore, Mysore 570 006, India b Institut TELECOM, TELECOM and Management, SudParis, France c Channabasaveshwara Institute of Technology, Gubbi 572 216, India |
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Abstract: | In this paper, we address the problem of designing efficient fusion schemes of complementary biometric modalities such as face and palmprint, which are effectively coded using Log-Gabor transformations, resulting in high dimensional feature spaces. We propose different fusion schemes at match score level and feature level, which we compare on a database of 250 virtual people built from the face FRGC and the palmprint PolyU databases. Moreover, in order to reduce the complexity of the fusion scheme, we implement a particle swarm optimization (PSO) procedure which allows the number of features (identifying a dominant subspace of the large dimension feature space) to be significantly reduced while keeping the same level of performance. Results in both closed identification and verification rates show a significant improvement of 6% in performance when performing feature fusion in Log-Gabor space over the more common optimized match score level fusion method. |
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Keywords: | Multimodal biometrics Feature level fusion Feature selection Particle swarm optimization Match score level fusion |
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