Lanczos Algorithm for 2DPCA
Xuansheng Wang, Huazhong Li, Yanbing Zhou, Hongying Zheng · Journal of Physics Conference Series · 2021
Abstract The traditional PCA algorithm (Principle Component Analysis) can obtain the feature space of face image and realize face recognition by expanding the face image matrix into vectors in face recognition. 2DPCA (Two-dimensional Principle Component Analysis) doesn’t need to spread the image matrix into one-dimensional vectors. The covariance matrix is constructed directly by using two-dimensional image matrix, so that the calculation of eigenvalue and eigenvector is simplified. We apply the Lanczos algorithm to 2 DPCA in this paper for Indian faces. The numerical experiments show that our method runs much faster and gets better recognition rates than the traditional 2DPCA algorithm.