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A probabilistic neural network for face detection on segmented skin areas based on fuzzy rules

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7 Author(s)
Anagnostopoulos, C. ; Dept. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Greece ; Anagnostopoulos, I. ; Vergados, D. ; Papaleonidopoulos, I.
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In this paper, the problem of face detection in color images is addressed. Unlike in face recognition, where the classes to be discriminated are different faces, in face detection, the two classes to be discriminated are "face area" and "non-face area". A novel approach to face detection is presented, which is based on a probabilistic neural network (PNN) specially trained for the identification of faces from skin areas within the image plane, which were previously located using fuzzy logic rules. The performance of the whole system was tested using 137 color image scenes with various illumination conditions containing human faces. The images were taken with a common digital camera, at a resolution of 1280×960 pixels. The PNN coupled with the fuzzy logic rules become the basis for developing a computer-based face detection system, whose overall identification performance was 85.2%. One limitation of the system is that it is. restricted only in detection of frontal human faces.

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Electrotechnical Conference, 2002. MELECON 2002. 11th Mediterranean

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