Designing efficient fusion schemes for multimodal biometric systems using face and palmprint

Authors:
R. Raghavendra;Bernadette Dorizzi;Ashok Rao;G. Hemantha Kumar
Affiliations:
Department of Studies in Computer Science, University of Mysore, Mysore 570 006, India and Institut TELECOM, TELECOM and Management, SudParis, France;Institut TELECOM, TELECOM and Management, SudParis, France;Channabasaveshwara Institute of Technology, Gubbi 572 216, India;Department of Studies in Computer Science, University of Mysore, Mysore 570 006, India
Venue:
Pattern Recognition
Year:
2011

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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.