Generalization of the Lambertian model and implications for machine vision
International Journal of Computer Vision
What is the set of images of an object under all possible lighting conditions?
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Lighting Normalization with Generic Intrinsic Illumination Subspace for Face Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Generalized Discriminant Analysis Using a Kernel Approach
Neural Computation
Total Variation Models for Variable Lighting Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition under varying illumination using gradientfaces
IEEE Transactions on Image Processing
Face recognition under varying lighting conditions using self quotient image
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Face recognition is very useful in many applications, such as safety and surveillance, intelligent robot, and computer login. The reliability and accuracy of such systems will be influenced by the variation of background illumination. Therefore, how to accomplish an effective illumination compensation method for human face image is a key technology for face recognition. Our study uses several computer vision techniques to develop an illumination compensation algorithm to processing the single channel (such as grey level or illumination intensity) face image. The proposed method mainly consists of four processing modules: (1) Homomorphic Filtering, (2) Ratio Image Generation, and (3) Anisotropic Smoothing. Experiments have shown that by applying the proposed method the human face images can be further recognized by conventional classifiers with high recognition accuracy.