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Face recognition algorithm using extended vector quantization histogram features

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  • Yan Yan
  • Feifei Lee
  • Xueqian Wu
  • Qiu Chen

Abstract

In this paper, we propose a face recognition algorithm based on a combination of vector quantization (VQ) and Markov stationary features (MSF). The VQ algorithm has been shown to be an effective method for generating features; it extracts a codevector histogram as a facial feature representation for face recognition. Still, the VQ histogram features are unable to convey spatial structural information, which to some extent limits their usefulness in discrimination. To alleviate this limitation of VQ histograms, we utilize Markov stationary features (MSF) to extend the VQ histogram-based features so as to add spatial structural information. We demonstrate the effectiveness of our proposed algorithm by achieving recognition results superior to those of several state-of-the-art methods on publicly available face databases.

Suggested Citation

  • Yan Yan & Feifei Lee & Xueqian Wu & Qiu Chen, 2018. "Face recognition algorithm using extended vector quantization histogram features," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-24, January.
    • Handle: RePEc:plo:pone00:0190378
    DOI: 10.1371/journal.pone.0190378
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