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GA-ANN based technique for face recognition : PCA features vs average grey level value features (2005)

Abstract

This paper investigates a feature selection and classification technique for face recognition using genetic algorithms and artificial neural networks. The experiments using average grey level value features and PCA features have been conducted on a face image dataset which is extracted from FERET benchmark database. For average grey level value features experiments, different sizes of feature extraction areas and different feature combination sequences are investigated. The effects of aging process on the proposed technique are also investigated. A detailed comparative analysis of experimental results is included in this paper.

Publication details

Download	http://hdl.cqu.edu.au/10018/29111
Publisher	Sydney : UTS,
Repository	ARROW Discovery Service (Australia)
Keywords	Application tools and system utilities. (700102), Neural Networks, Genetic Algorithms and Fuzzy Logic. (280212), TBA., Application Tools and System Utilities. (890202), Computer Software and Services. (8902), Information and Communication Services. (89), Neural, Evolutionary and Fuzzy Computation. (080108), Artificial Intelligence and Image Processing. (0801), Information and Computing Sciences. (08), Pattern recognition systems., Algorithms., Neural networks (Computer science)
Type	conference paper
Language	en-aus
Relation	Workshop on Learning Algorithms for Pattern Recognition : in conjunction with the 18th Australian Joint Conference on Artificial Intelligence / Ghosh, Ranadhir(ed), Verma, Brijesh(ed). Sydney. : UTS, 2005. p. 8-14 7 pages Refereed 1863657150, ACQUIRE [electronic resource] : Central Queensland University Institutional Repository.