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This paper describes an illumination normalization technique which works at the pre-processing stage where the face image is first divided into equal sub-regions. Each sub-region is then processed separately for illumination normalization. Then the segments are joined back followed by further processing like noise removal and contrast enhancement. The proposed technique is tested on Yale dataset and...
The main problem of face detection is illumination, pose, facial expression, etc; every face detection algorithms are focused on solving these problems, which algorithm can solve these problems very well, so then this algorithm will be given a higher detection rate and a lower of false detecting rate. In this paper, a new face detection algorithm is introduced, which combined the skin color segmentation...
Recognizing human faces in various lighting conditions is quite difficult for a surveillance system. The problem becomes more difficult if face images are taken in extremely high dynamic range scenes. Most of automatic face recognition systems assume the images are taken under well controlled illumination. The face segmentation as well as recognition problem is much simpler under such a constrained...
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