关键词: 特征提取, 线性降维, Fisher判别准则, 因子分析, 人脸识别

Abstract: The stability and discrimination of low-dimensional feature extracting?are the key problems in the study of the pattern recognition. In terms of the practical application, this paper puts forward the discriminate criterion based on factors analysis and the in-depth study of Fisher discriminate criterion. It aims to solve the problem of the suboptimal definition for Fisher criterion with between-class scatter matrix and within-class scatter matrix. The experimental comparison between the synthetic data and real face data sets demonstrates that the presented algorithm possesses better robustness to deal with the data centralized edge and facial variations of expressions or poses than Fisher discriminate criterion.

Key words: feature extraction, linear dimension reduction, Fisher criterion, factors analysis, face recognition