Abstract
human face recognition is a hard topic because of the multitude of parameters involved (e.g. variation in pose, illumination, facial expression, partial occlusions), it is very important to be interested and to invest in it viewed her many fields of application (identity authentication, physical and logical access control, video surveillance, human-machine interface...). The work presented in this paper is in this context. Its objective is the implementation of a complete architecture of a robust face recognition system. In a first time, a new approach has been developed for the detection of faces in a 2D color image. Secondly, is focused on the feature extraction using an original approach which includes the Gabor descriptor and a pose estimator. Finally, to validate this research, the developed system is tested on standard databases: Caltech_Web, AT&T and Color FERET. Keywordsrecognition, face detection, Gabor wavelets, pose estimator, Supports Vectors Machines.
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