Multi-scale Local Binary Pattern Histograms for Face Recognition

  • Chi-Ho Chan
  • Josef Kittler
  • Kieron Messer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4642)


A novel discriminative face representation derived by the Linear Discriminant Analysis (LDA) of multi-scale local binary pattern histograms is proposed for face recognition. The face image is first partitioned into several non-overlapping regions. In each region, multi-scale local binary uniform pattern histograms are extracted and concatenated into a regional feature. The features are then projected on the LDA space to be used as a discriminative facial descriptor. The method is implemented and tested in face identification on the standard Feret database and in face verification on the XM2VTS database with very promising results.


Face Recognition Linear Discriminant Analysis Recognition Rate Face Image Local Binary Pattern 
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

  • Chi-Ho Chan
    • 1
  • Josef Kittler
    • 1
  • Kieron Messer
    • 1
  1. 1.Centre for Vision, Speech and Signal Processing, University of SurreyUnited Kingdom

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