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Face recognition methods based on principal component analysis and feedforward neural networks

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2 Author(s)
M. Oravec ; Dept. of Telecommun., Slovak Tech. Univ., Bratislava, Slovakia ; J. Pavlovicova

In this paper, human face as biometric is considered. Original method of feature extraction from image data is introduced using MLP (multilayer perceptron) and PCA (principal component analysis). This method is used in human face recognition system and results are compared to face recognition system using PCA directly, to a system with direct classification of input images by MLP and RBF (radial basis function) networks, and to a system using MLP as a feature extractor and MLP and RBF networks in the role of classifier. In order to obtain deeper insight into eight presented methods, also visualizations of internal representation of input data obtained by neural networks are presented.

Published in:

Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on  (Volume:1 )

Date of Conference:

25-29 July 2004