Abstract: With the application of two-dimensional principal component analysis (PCA) in face recognition,a lot of ana-lysis methods based on 2D are becoming more popular.Compared with PCA algorithm based on vector feature extraction,2DPCA algorithm is based on the feature extraction of the matrix.Unlike the methods depending on the columns or all matrix of the eigenmatrix ,we proposed an algorithm based on the distance measurement method of the characteristic matrix,and the algorithm is combined with KNN algorithm.By using this method,the shortcoming based on the 2DPCA algorithm compared with algorithm based on principal component analysis (PCA) can alleviate some problems needed to be more coefficient.Experimental results on face database show that the proposed method of distinguish accuracy will increase,is’s performance is better than other methods in terms of accuracy and storage capacity.

Key words: 2DPCA,Face recognition,Row-KNN