关键词: 主成分分析, 独立分量分析, 线性判别分析, 遗传算法

Abstract: Class discriminant ability of the feature and the feature space is put forward to analyze the performance of the feature spaces given by PCA，ICA and LDA，and then diagram form is drawn to compare the discriminant ability of the above three methods.Genetic algorithm is improved to avoid “over-fitting”.At last，a new face feature extraction method which is high order independent and can evaluate the class information is brought forward：ICA is used to extract high order independent features which are used as the original solution set and improved GA has been adopted to combine class information.Experimental results show that the scheme can obtain good results.

Key words: principal component analysis, independent component analysis, linear discriminant analysis, genetic algorithm