Binary two-dimensional PCA

Publication Type:
Journal Article
Citation:
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2008, 38 (4), pp. 1176 - 1180
Issue Date:
2008-08-01
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2011000282OK.pdf363.45 kB
Adobe PDF
Fast training and testing procedures are crucial in biometrics recognition research. Conventional algorithms, e.g., principal component analysis (PCA), fail to efficiently work on large-scale and high-resolution image data sets. By incorporating merits from both two-dimensional PCA (2DPCA)-based image decomposition and fast numerical calculations based on Haarlike bases, this technical correspondence first proposes binary 2DPCA (B-2DPCA). Empirical studies demonstrated the advantages of B-2DPCA compared with 2DPCA and binary PCA. © 2008 IEEE.
Please use this identifier to cite or link to this item: