Adaptive Context-Aware Filter Fusion for Face Recognition on Bad Illumination

  • Nam Mi Young
  • Md. Rezaul Bashar
  • Phill Kyu Rhee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4251)


At present, the performance of face recognition system depends much on the variations in illumination. To solve this problem, this paper presents an adaptable face recognition approach that uses filter fusion representation. The key idea is to use context-aware filter fusion to get better image from a bad illumination one. Genetic algorithm is the tool for adaptation for individual context category. These can provide robust face recognition on illumination context-awareness under uneven environments. Gabor wavelet representation can also provide a robust feature for image enhancement. Using these approaches, we have developed a robust face recognition technique that can recognize with a notable success and it has been tested on Inha DB and FERET face images.


Face Recognition Face Image Histogram Equalization Gabor Wavelet Fiducial Point 
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 2006

Authors and Affiliations

  • Nam Mi Young
    • 1
  • Md. Rezaul Bashar
    • 1
  • Phill Kyu Rhee
    • 1
  1. 1.Intelligent Technology Laboratory, Dept. of Computer Science & EngineeringInha UniversityIncheonKorea

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