Pattern Recognition Using Evolutionary Classifier and Feature Selection.

In this paper, we propose face feature selection and classifier selection method for face image group according illuminant. In knowledge based, we stored context and weight for feature points and selected classifier for context. This context is distinguished the face images having varying illumination. This context knowledge can be accumulated and used later. Therefore we designed the face recognition system by using evolution method and efficient face feature point selection. It can improve its performance incrementally using proposed algorithm. And we proposed efficient context modeling method by using SOM. For context awareness, we made artificial face images from FERET fa dataset and divided several group. Therefore we improved face recognition ratio using adaptable classifier, feature and weight for feature points. [ABSTRACT FROM AUTHOR]