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Discrimination and detection of face and non-face using multilayer feedforward perceptron

Publication Type : Journal Article

Publisher : Advances in Intelligent Systems and Computing

Source : Advances in Intelligent Systems and Computing, Springer Verlag, Volume 397, p.89-103 (2016)

Url : http://www.scopus.com/inward/record.url?eid=2-s2.0-84955286682&partnerID=40&md5=cf076781de89ad9b2a94e69dfddb3538

ISBN : 9788132226697

Keywords : Computer vision, Face detection system, Face images, Face recognition, Facial feature, Feature vectors, Filter extracts, Gabor filters, High-accuracy, Illumination changes, Image processing, Multilayer feedforward, Multilayers, Pattern recognition, Soft computing

Campus : Coimbatore

School : School of Engineering

Department : Computer Science, Sciences

Year : 2016

Abstract : The paper proposes a face detection system that locates and extracts faces from the background using the multilayer feedforward perceptron. Facial features are extracted from the local image using filters. In this approach, feature vector from Gabor filter acts as an input for the multilayer feedforward perceptron. The points holding high information on face image are used for extraction of feature vectors. Since Gabor filter extracts features from varying scales and orientations, the feature points are extracted with high accuracy. Experimental results show the multilayer feedforward perceptron discriminates and detects faces from non-face patterns irrespective of the illumination changes. © Springer India 2016.

Cite this Research Publication : K. S. Gautam and Dr. Senthil Kumar T., “Discrimination and detection of face and non-face using multilayer feedforward perceptron”, Advances in Intelligent Systems and Computing, vol. 397, pp. 89-103, 2016.

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