Binary two-dimensional PCA

Pang, Y. and Tao, D. and Yuan, Y. and Li, Xuelong (2008) Binary two-dimensional PCA. Transactions on Systems, Man, and Cybernetics 38 (4), pp. 1176-1180. ISSN 1083-4419.

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Official URL: http://dx.doi.org/10.1109/TSMCB.2008.923151

Abstract

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.

Metadata

Item Type:	Article
School:	School of Business, Economics & Informatics > Computer Science and Information Systems
Depositing User:	Sarah Hall
Date Deposited:	12 Jul 2013 13:19
Last Modified:	11 Oct 2016 15:27
URI:	https://eprints.bbk.ac.uk/id/eprint/7674

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