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Person identification plays a major role in any secured and safety system. Face is one of the major biometric explored by many researchers for human identification. The problem becomes more complex by means of any occlusion of objects, due to different illumination, expression and pose. We propose a novel pattern recognition approach for face detection in this paper. The approach presented is an amalgamation of artificial neural networks and fuzzy set theory. The proposed method runs in two phases and fuses the results for better performance and accuracy. The proposed method has been tested on BioID dataset and got 94% accuracy.