Face Recognition Using Plurality Voting and Collaborative Representation based on the Bit-plane Information

As a new representation technique, collaboration representation is used to represent the test sample with all training samples from all classes. Plurality voting is one of the most widely used combination strategies in pattern recognition. This paper presents a new and an efficient face recognition approach using plurality voting and collaboration representation based on the binary bit-plane images. First, face gray images are equalized and decomposed. Next,employing collaboration representation and the corresponding five bit-plane images which have more discrimination information,five identities about the same test image can be obtained. Finally, these five identities vote to the true identity of the test image. If the plurality voting fails, the true identity of the test image will be decided by virtual weight sum face images constructed by 8 bit-plane images with collaboration representation. Weight vector, which is important for the virtual images, is determined by the recognition rate and the order of bit planes. The extensive experiments demonstrate the proposed approach has the higher right recognition accuracy and its speed is faster than the SRC prominently.