Why the alternative PCA provides better performance for face recognition

This paper presents an alternative to PCA technique, called as APCA, which uses within class scatter rather than global covariance matrix. The APCA technique produces better features cluster than does common PCA (CPCA) because it keep the null spaces which contain good discriminant information. The proposed technique achieves better performance for both recognition rate and accuracy parameters than those of CPCA when it was tested using several databases (ITS-LAB., INDIA, ORL, and FERET).