Abstract
Face recognition accuracy is determined by face detection results. Detected faces will be in view of clear and occlusion faces. If detected face has occlusion than recognition accuracy is reduced. This research is directed to increase recognition rate when detected occlusion face. In this paper is proposed normalization occlusion faces by Principal component analysis algorithm. After applying normalization method in occlusion faces false reject error rate is decreased.
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