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Multibiometric System Using Level Set Method and Particle Swarm Optimization

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Image Analysis and Recognition (ICIAR 2012)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7325))

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Abstract

Multibiometric systems alleviate some of the drawbacks possessed by the single modal biometric trait and provide better recognition accuracy. This paper presents a multimodal system that integrates the iris, face, and gait features based on the fusion at feature level. The novelty of this research effort is that a feature subset selection scheme based on Particle Swarm Optimization (PSO) is proposed to select the optimal subset of features from the fused feature vector. In addition, we apply a Variational Level Set (VLS)-based curve evolution scheme to detect the silhouette shape structure. Experimental results indicate that the proposed approach increases biometric recognition accuracies compared to that produced by single modal biometrics.

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Author information

Authors and Affiliations

  1. Centre for Pattern Analysis and Machine Intelligence, University of Waterloo, ON, Canada

    Kaushik Roy & Mohamed S. Kamel

Authors
  1. Kaushik Roy
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  2. Mohamed S. Kamel
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Editor information

Editors and Affiliations

  1. Faculty of Engineering, Institute of Biomedical Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio Campilho

  2. Department of Electrical and Computer Engineering, University of Waterloo, N2L 3G1, Waterloo, ON, Canada

    Mohamed Kamel

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© 2012 Springer-Verlag Berlin Heidelberg

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Roy, K., Kamel, M.S. (2012). Multibiometric System Using Level Set Method and Particle Swarm Optimization. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2012. Lecture Notes in Computer Science, vol 7325. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31298-4_3

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  • DOI: https://doi.org/10.1007/978-3-642-31298-4_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31297-7

  • Online ISBN: 978-3-642-31298-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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