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Face recognition across illumination

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Abstract

Illumination variation on images of faces is one of the most difficult problems in face recognition systems. The performance of a self-organizing map-based face recognition system is highly degraded when the illumination in test images differs from that of the training images. Illumination normalization is a way to solve this problem. Both global and local image enhancement methods are studied in this article. A local histogram equalization method strongly improves the recognition accuracy of the CMU-PIE face database.

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Authors and Affiliations

  1. Department of Intelligent Systems, Graduate School of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka, 819-0395, Japan

    Saleh Aly, Alaa Sagheer & Rin-ichiro Taniguchi

  2. Department of Electronics Engineering and Computer Science, Fukuoka University, Fukuoka, Japan

    Naoyuki Tsuruta

Authors
  1. Saleh Aly
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  2. Alaa Sagheer
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  3. Naoyuki Tsuruta
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  4. Rin-ichiro Taniguchi
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Corresponding author

Correspondence to Saleh Aly.

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Cite this article

Aly, S., Sagheer, A., Tsuruta, N. et al. Face recognition across illumination. Artif Life Robotics 12, 33–37 (2008). https://doi.org/10.1007/s10015-007-0437-9

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  • DOI: https://doi.org/10.1007/s10015-007-0437-9

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