Multi-resolution Histograms of Local Variation Patterns (MHLVP) for Robust Face Recognition

  • Wenchao Zhang
  • Shiguang Shan
  • Hongming Zhang
  • Wen Gao
  • Xilin Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3546)


This paper presents a novel approach to face recognition, named Multi-resolution Histograms of Local Variation Patterns (MHLVP), in which face images are represented as the concatenation of the local spatial histogram of local variation patterns computed from the multi-resolution Gabor features. For a face image with abundant texture and shape information, aGabor feature map(GFM) is computed by convolving the image with each of the forty multi-scale and multi-orientation Gabor filters. Each GFM is then divided into small non-overlapping regions to enhance its shape information, and then Local Binary Pattern (LBP) histograms are extracted for each region and concatenated into a feature histogram to enhance the texture information in the specific GFM. Further more, all of the feature histograms extracted from the forty GFMs are further concatenated into a single feature histogram as the final representation of the given face image. Eventually, the identification is achieved by histogram intersection operation. Our experimental results on FERET face databases show that the proposed method performs terrifically better than the performance of some classical results including the best results in FERET’97.


Face Recognition Face Image Local Binary Pattern Gabor Filter Gabor Feature 
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 2005

Authors and Affiliations

  • Wenchao Zhang
    • 1
  • Shiguang Shan
    • 2
  • Hongming Zhang
    • 1
  • Wen Gao
    • 2
  • Xilin Chen
    • 1
    • 2
  1. 1.School of Computer Science and TechnologyHarbin Institute of TechnologyHarbinP.R. China
  2. 2.ICT-ISVISION Joint R&D Laboratory for Face RecognitionCASBeijingP.R. China

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