JOURNAL ARTICLE

Face Recognition Based on Radial Basis Function Neural Networks

Abstract

The face recognition is an active subject in the area of computer pattern recognition, which has been a focus in reach for the last couple of decades because of its widely potential applications. A face recognition approach is put forward based on the RBF neural network. Also discussed are the problem of feature of a face image vector, the problem of normalization of the image-size, and the problem of training algorithm of hidden layerpsilas neural nodes. Experiments have been conducted on ORL face database. The results show that compared with BP neural network, the RBF neural network can decrease the error rate, the training time, and the recognition time efficiently.

Keywords:
Normalization (sociology) Computer science Facial recognition system Artificial neural network Artificial intelligence Pattern recognition (psychology) Time delay neural network Radial basis function Face (sociological concept) Probabilistic neural network Feature (linguistics) Feature vector Feedforward neural network Feature extraction Neocognitron

Metrics

7
Cited By
0.29
FWCI (Field Weighted Citation Impact)
14
Refs
0.70
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Face and Expression Recognition
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Video Stabilization
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Face recognition and analysis
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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