Binary two-dimensional PCA

Yanwei Pang, Dacheng Tao, Yuan Yuan, Xuelong Li

科研成果: 期刊稿件文章同行评审

77 引用 (Scopus)

摘要

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.

源语言英语
页(从-至)1176-1180
页数5
期刊IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
38
4
DOI
出版状态已出版 - 8月 2008
已对外发布

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