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Robust Face Recognition Using Color Information

  • Zhiming Liu
  • Chengjun Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5558)

Abstract

This paper presents a robust face recognition method using color information with the following three-fold contributions. First, a novel hybrid color space, the RC r Q color space, is constructed out of three different color spaces: the RGB, YC b C r , and YIQ color spaces. The RC r Q hybrid color space, whose component images possess complementary characteristics, enhances the discriminating power for face recognition. Second, three effective image encoding methods are proposed for the component images in the RC r Q hybrid color space: (i) a patch-based Gabor image representation for the R component image, (ii) a multi-resolution LBP feature fusion scheme for the C r component image, and (iii) a component-based DCT multiple face encoding for the Q component image. Finally, at the decision level, the similarity matrices generated using the three component images in the RC r Q hybrid color space are fused using a weighted sum rule. The most challenging Face Recognition Grand Challenge (FRGC) version 2 Experiment 4 shows that the proposed method, which achieves the face verification rate of 92.43% at the false accept rate of 0.1%, performs better than the state-of-the-art face recognition methods.

Keywords

Face Recognition Color Space Face Image Local Binary Pattern Component Image 
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 2009

Authors and Affiliations

  • Zhiming Liu
    • 1
  • Chengjun Liu
    • 1
  1. 1.Department of Computer ScienceNew Jersey Institute of TechnologyNewark, New JerseyUSA

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