Local Illumination Normalization and Facial Feature Point Selection for Robust Face Recognition


  • Song HAN KIM IL SUNG University, Pyongyang
  • Jinsong KIM
  • Cholhun KIM
  • Jongchol JO


Face recognition, Illumination normalization, Robustness, Gabor wavelet, Feature point, ICA, HMM, AAM


Face recognition systems must be robust to the variation of various factors such as facial expression, illumination, head pose and aging. Especially, the robustness against illumination variation is one of the most important problems to be solved for the practical use of face recognition systems. Gabor wavelet is widely used in face detection and recognition because it gives the possibility to simulate the function of human visual system. In this paper, we propose a method for extracting Gabor wavelet features which is stable under the variation of local illumination and show experiment results demonstrating its effectiveness.


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How to Cite

HAN, S., KIM, J., KIM, C., & JO, J. (2013). Local Illumination Normalization and Facial Feature Point Selection for Robust Face Recognition. Journal of Mobile, Embedded and Distributed Systems, 5(1), 6-10. Retrieved from http://jmeds.eu/index.php/jmeds/article/view/Facial_Feature_Point_Selection_for_Robust_Face_Recognition