Modular complete 2DPCA and its application in face recognition

摘要

An improved modular complete 2DPCA method was proposed. Firstly, the original images are divided into sub-images in proposed approach. The best projecting matrix from general matrix that is made up of all normalized sub-images could be obtained accordingly. Secondly, when all sub-images of training samples and testing samples were projected to the best projecting matrix, the recognition features was produced. Finally, the nearest distance classification was used to distinguish each face. The experiment results on ORL face database indicate that the modular complete 2DPCA is obviously superior to modular 2DPCA.