Completed Local Binary Count for Rotation Invariant Texture Classification

In this brief, a novel local descriptor, named local binary count (LBC), is proposed for rotation invariant texture classification. The proposed LBC can extract the local binary grayscale difference information, and totally abandon the local binary structural information. Although the LBC codes do n...

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Veröffentlicht in:IEEE transactions on image processing 2012-10, Vol.21 (10), p.4492-4497
Hauptverfasser: YANG ZHAO, HUANG, De-Shuang, WEI JIA
Format: Artikel
Sprache:eng
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Zusammenfassung:In this brief, a novel local descriptor, named local binary count (LBC), is proposed for rotation invariant texture classification. The proposed LBC can extract the local binary grayscale difference information, and totally abandon the local binary structural information. Although the LBC codes do not represent visual microstructure, the statistics of LBC features can represent the local texture effectively. In addition, a completed LBC (CLBC) is also proposed to enhance the performance of texture classification. Experimental results obtained from three databases demonstrate that the proposed CLBC can achieve comparable accurate classification rates with completed local binary pattern.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2012.2204271