Constructing a fuzzy grammar for syntactic face detection
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This paper presents a structural face detection system. The proposed system consists of three stages; pre-processing, face-components extraction, and final decision-making. In the first stage, image conversion, colour operation, image restoration, and image enhancement are carried out. Face components are extracted in the second stage. A face model is defined, and a fuzzy grammar composed of octal chain codes is used to represent each of the seven face components. The practical limitations of this representation are considered. Structural components are detected, and the possibility degree that the extracted component is a real face component is determined. In the last stage, a commonsense knowledge base is employed for final evaluation. The detected face components and their corresponding possibility degrees allow the human face knowledge base to locate faces in the image and generate a membership degree for that face within the face class. The experimental results obtained using this method are presented.