The application of neural network and wavelet in human face illumination compensation

  • Authors:
  • Zhongbo Zhang;Siliang Ma;Danyang Wu

  • Affiliations:
  • Department of Mathematics, Jilin University, Changchun, China;Department of Mathematics, Jilin University, Changchun, China;Department of Mathematics, Jilin University, Changchun, China

  • Venue:
  • ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
  • Year:
  • 2005

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Abstract

The performance of face recognition system is greatly affected by the illumination changes. In this article, we propose a method of face illumination compensation based on neural network and wavelet. It sufficiently combines multi-resolution analysis of wavelet and the selfadaptation learning and good spread ability of BP neural network, thus this method carries out the face illumination compensation. The theory and experiments prove that this method solves the problem of illumination compensation efficiently in the face detection and recognition process. It improves the face detection and recognition under different illumination conditions. Moreover, it has good robustness and can be used in a wide range.