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SVM-Based Selection of Colour Space Experts for Face Authentication

  • Mohammad T. Sadeghi
  • Samaneh Khoshrou
  • Josef Kittler
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4642)

Abstract

We consider the problem of fusing colour information to enhance the performance of a face authentication system. The discriminatory information potential of a vast range of colour spaces is investigated. The verification process is based on the normalised correlation in an LDA feature space. A sequential search approach which is in principle similar to the “plus L and take away R” algorithm is applied in order to find an optimum subset of the colour spaces. The colour based classifiers are combined using the SVM classifier. We show that by fusing colour information using the proposed method, the resulting decision making scheme considerably outperforms the intensity based verification system.

Keywords

Support Vector Machine Linear Discriminant Analysis Face Image Fusion Rule False Acceptance Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Mohammad T. Sadeghi
    • 1
  • Samaneh Khoshrou
    • 1
  • Josef Kittler
    • 2
  1. 1.Signal Processing Research Lab., Department of Electronics, University of Yazd, YazdIran
  2. 2.Centre for Vision, Speech and Signal Processing, School of Electronics and Physical Sciences, University of Surrey, Guildford GU2 7XHUK

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