关键词: 人脸识别, 二维主成分分析, 样本中间值, 特征提取

Abstract: Under the condition of small sample size，the average of all training samples used in the traditional principal component analysis algorithm is not always the scatter center of the samples.To address the problem，a new two dimension principal component analysis method based on the sample median is proposed.This algorithm is called Median Two Dimension Principal Component Analysis（M2DPCA），in which the median of training samples is substituted for the average.To demonstrate the effectiveness of the method，extensive experiments are performed on two popular face databases，such as ORL and FERET.Experiment results indicate that the proposed method is better than traditional PCA and 2DPCA.

Key words: face recognition, Two-Dimension Principal Component Analysis（2DPCA）, sample median, feature extraction