Algorithms of two-dimensional principal component analysis for face recognition

In article presents algorithms for two-dimensional principal component analysis (Two-dimensional Principal Component Analysis - 2D PCA)-oriented processing of digital images of large sizes in a small sample. Algorithms based on direct calculation of two covariance matrices for all source images without converting them into vectors. Result analysis - finding the principal components for the rows and columns of the source images and the construction of the corresponding matrices of two-dimensional projection. We discuss two ways to do 2D PCA, corresponding to parallel and cascade forms of its realization. Evaluated the presented algorithms.