关键词: 散布矩阵, 主成分分析, 本征向量, 特征提取

Abstract: In this paper，a generalized principle component analysis for feature extraction is proposed.First，image matrixes are reshaped in proposed method.Then，an image scatter matrix is constructed using the reshaped image matrixes and its eigenvectors are derived for image feature extraction.The generalized principle component analysis is an extension of two-dimensional PCA and modular two-dimensional PCA.Scatter matrix with random size can be constructed using the method.So，the dimension of projection vector can change according need.Experiment results show that the generalized principle component analysis can extract better feature value and has higher performance efficiency with the reduction of scatter matrix size.

Key words: scatter matrix, principal component analysis, eigenvector, feature extraction