Face Recognition Algorithm Based on Algebraic Features of SVD and KL Projection

摘要

In this paper, a new approach of face recognition is presented on the basis of PCA face recognition algorithm. It constructs a new face recognition feature vector based on fusion algebraic features extracted from singular value decomposition and KL projection. In this method, singular value decomposition and KL transform are applied to the face image, then the main feature and SVD feature vector of KL projection are fused to form a new face recognition feature vector. The method can effectively eliminate the influence of the correlation between the face images and the recognition accuracy, which greatly improves the accuracy of face recognition.