Algorithms of two-dimensional principal component analysis for face recognition
G.A. Kukharev, N.L. Shchegolev

V.A. Kotelnikov Institute of Radio Engineering and Electronics of Russian Academy of Sciences, Ulyanovsk Branch,
Ulyanovsk State University,
Ulyanovsk State Technical University

Full text of article: Russian language.

Abstract:
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.

Key words:
principal component analysis, image recognition.

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