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Adaptive Weber-face for robust illumination face recognition

  • Chao YangEmail author
  • Shiqian Wu
  • Hongping Fang
  • Meng Joo Er
Article
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Abstract

In this paper, an adaptive Weber-face method is presented to deal with varying lighting and extract illumination-insensitive representation for face recognition. A novel pixel-wise adaptive gamma transformation, which has been proved mathematically, is proposed to achieve a local uniform-illumination assumption in Weber-face. Next, the local binary patterns are extracted from the Weber-face images, and then further alleviate the effect of varying illumination. Experiments demonstrate that the proposed method achieves the high recognition rates of 99.55% and 96.63% on extended Yale B and CMU-PIE databases respectively, which outperforms the state-of-the-art methods.

Keywords

Face recognition Illumination normalization Adaptive Weber-face Gamma correct Local binary patterns 

Notes

Acknowledgements

This work is supported in part by the National Natural Science Foundation of China under Grant 61371190 and 61775172.

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Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2019

Authors and Affiliations

  • Chao Yang
    • 1
    Email author
  • Shiqian Wu
    • 1
  • Hongping Fang
    • 2
  • Meng Joo Er
    • 3
  1. 1.School of Machinery and AutomationWuhan University of Science and TechnologyWuhanChina
  2. 2.School of Information Science and EngineeringWuhan University of Science and TechnologyWuhanChina
  3. 3.School of Electrical and Electronic EngineeringNanyang Technological UniversitySingaporeSingapore

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