Face Recognition Based on Weighted Maximum Margin Criterion
Xin Wang · Jisuanji gongcheng · 2008
Feature extraction techniques are widely employed in face recognition system to reduce the dimensionality of data and to enhance the discriminatory information.In this paper,a new feature extraction method——Weighted Maximum Margin Criterion(WMMC) is proposed,which is an extension of Maximum Margin Criterion(MMC).The inter-class and between-class scatter matrix are weighted separately by a weighting function.An efficient face recognition system is designed by using Discrete Wavelet Transform(DWT),Principal Component Analysis(PCA) and WMMC.Experimental results on ORL database show that the proposed algorithm improves the performance of face recognition significantly and achieves the highest recognition rate to 98.25%.