Face Recognition Methods Based on Feedforward Neural Networks, Principal Component Analysis and Self-Organizing Map
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Date
2007-04
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Referee
Mark
Journal Title
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Společnost pro radioelektronické inženýrství
Abstract
In this contribution, 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. Also a two-stage method for face recognition is presented, in which Kohonen self-organizing map is used as a feature extractor. MLP and RBF network are used as classifiers. In order to obtain deeper insight into presented methods, also visualizations of internal representation of input data obtained by neural networks are presented.
Description
Citation
Radioengineering. 2007, vol. 16, č. 1, s. 51-57. ISSN 1210-2512
http://www.radioeng.cz/fulltexts/2007/07_01_51_57.pdf
http://www.radioeng.cz/fulltexts/2007/07_01_51_57.pdf
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Peer-reviewed
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en