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Face recognition : a new feature selection and classification technique (2004)

Abstract
A novel feature selection and classification technique for face recognition is presented this paper. Genetic Algorithms (GAs) for feature selection and Artificial Neural Network (ANN) for classification are incorporated in the proposed technique. The proposed GAs-ANN technique has two purposes in this research: 1) fusion and selection of features for face recognition. 2) location of significant areas inside ach facial region. Facial regions are identified by using distance threshold method based on center coordinate information of each facial region. The average grey level value feature is extracted from each facial region. Then these features are combined to form the input feature vector for the GAs-ANN technique. A set of experiments is conducted on a subset of the FERET database. The results show that the proposed approach is promising. A comnrehensive comparison with other existing face recognition approaches is included.

Publication details
Download http://hdl.cqu.edu.au/10018/16263
Publisher Rockhampton, Qld. : Central Queensland University,
Repository ARROW Discovery Service (Australia)
Keywords Human face recognition (Computer science), Application packages (700101), Image Processing (280203), TBA., Computer Gaming Software. (890203), Computer Software and Services. (8902), Information and Communication Services. (89), Image Processing. (080106), Artificial Intelligence and Image Processing. (0801), Information and Computing Sciences. (08), Image processing., Artificial intelligence., Computer science.
Type conference paper
Language en-aus
Relation Complex 2004 : Proceedings of the 7th Asia-Pacific Complex Systems Conference, Cairns Convention Centre, Cairns, Australia, 6-10 December 2004. Rockhampton, Qld. : Central Queensland University, 2004. p. 713-721 9 pages Refereed 1876674962, ACQUIRE [electronic resource] : Central Queensland University Institutional Repository.