TY - JOUR

T1 - Application of two-dimensional principal component analysis for recognition of face images

AU - Shchegoleva, N. L.

AU - Kukharev, G. A.

PY - 2010/12/27

Y1 - 2010/12/27

N2 - A two-dimensional principal component analysis (2D PCA) method directed at processing digital images is discussed. The method is based on representation of images as a set of rows and columns analyzing these sets. Two methods of realizing the 2D PCA corresponding to the parallel and cascade forms of its realization are presented, and their characteristics are estimated. The application of the 2D PCA method is shown for solving problems of representation and recognition of facial images. The experiments are fulfilled on ORL and FERET bases.

AB - A two-dimensional principal component analysis (2D PCA) method directed at processing digital images is discussed. The method is based on representation of images as a set of rows and columns analyzing these sets. Two methods of realizing the 2D PCA corresponding to the parallel and cascade forms of its realization are presented, and their characteristics are estimated. The application of the 2D PCA method is shown for solving problems of representation and recognition of facial images. The experiments are fulfilled on ORL and FERET bases.

KW - 2D PCA application

KW - Facial images recognition

KW - Parallel and cascade forms of 2D PCA realization

KW - Reduction of attribute space dimension

KW - Reduction of operational complexity

KW - Two-Dimensional Principal Component Analysis (2D PCA)

UR - http://www.scopus.com/inward/record.url?scp=78650366444&partnerID=8YFLogxK

U2 - 10.1134/S1054661810040127

DO - 10.1134/S1054661810040127

M3 - Article

AN - SCOPUS:78650366444

VL - 20

SP - 513

EP - 527

JO - Pattern Recognition and Image Analysis

JF - Pattern Recognition and Image Analysis

SN - 1054-6618

IS - 4

ER -