The face recognition is an active subject in the fields of computer vision and pattern recognition, which has a wide range of potential applications. In this paper, a method for color face recognition is presented, this algorithm extracts the final features by utilizing the techniques of the simulative K-L transform, the singular value decomposition, the principal component analysis and the Fisher linear discriminant analysis. Classifier in this algorithm can be simplified to make it more compact and effective, and higher correct recognition rate can be gained using less number of feature vectors. The effectiveness of the approach is experimentally demonstrated.