A comparison between linear and nonlinear principal component analysis using neural networks and a novel technique for face recognition

Authors:
Aryan Salmanpour;Saied Ali Saied Salehi
Affiliations:
Biomedical Engineering Department, Amirkabir University of Technology, Tehran Polytechnic, Tehran, Iran;Biomedical Engineering Department, Amirkabir University of Technology, Tehran Polytechnic, Tehran, Iran
Venue:
NN'05 Proceedings of the 6th WSEAS international conference on Neural networks
Year:
2005

Citing 5
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Abstract

In this paper, two new methods of face recognition are presented. First method has two stages for face recognition including feature extraction and their classification. Three feature extraction methods, statistical principal component analysis, linear and non-linear principal component analysis using neural networks and for classification a perceptron neural network with two hidden layers has been used in the first method. In the second method, many attempts were made for non-linear separation of person's data by their status data. The works were performed by neural networks through some innovative methods. In this model, 100 percentage of recognition rate orrectc for test sample of ORL face were achieved.