Title :
Face Recognition Based on 2DPCA under MMSE Rule and RBF Neural Network
Author :
Luo, Renze ; Ran, Ruisheng ; Wang, Ruyan
Author_Institution :
Electron. Eng. Dept., UESTC, Zhongshan
Abstract :
In this paper, based on the rule of minimal mean square error(MMSE), a method for face image feature extraction-2DPCA, is presented. Meanwhile, in theory, it is firstly proved that face feature extraction of 2DPCA ensures the energy lost is minimal and this method is reasonable; Then, RBF neural network is used to classify the test image. Experiment results show that, for the given threshold, the recognition rate of 2DPCA is about 95% and compared with PCA, much less running time is required for 2DPCA.
Keywords :
face recognition; feature extraction; image classification; mean square error methods; neural nets; principal component analysis; radial basis function networks; RBF neural network; feature extraction; feature extraction-2DPCA; image classification; minimal mean square error method; principal component analysis; radial basis function network; Computer science education; Educational technology; Electronic mail; Face recognition; Feature extraction; Mean square error methods; Neural networks; Optical scattering; Principal component analysis; Testing; 2DPCA; face recognition; the rule of MMSE;
Conference_Titel :
Education Technology and Computer Science, 2009. ETCS '09. First International Workshop on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-1-4244-3581-4
DOI :
10.1109/ETCS.2009.715
