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

Raghavendra, R. and Dorizzi, B. and Rao, A. and Kumar, G. H. (2011) Designing efficient fusion schemes for multimodal biometric systems using face and palmprint. PATTERN RECOGNITION, 44 (5). pp. 1076-1088. ISSN 0031-3203

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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. (C) 2010 Elsevier Ltd. All rights reserved.

Item Type:	Article
Uncontrolled Keywords:	Multimodal biometrics; Feature level fusion; Feature selection; Particle swarm optimization; Match score level fusion
Subjects:	D Physical Science > Computer Science
Divisions:	Department of > Computer Science
Depositing User:	Users 23 not found.
Date Deposited:	01 Jul 2019 05:36
Last Modified:	01 Jul 2019 05:36
URI:	http://eprints.uni-mysore.ac.in/id/eprint/2515

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