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Spatially weighted order binary pattern for color texture classification
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DOI：10.1016/j.eswa.2019.113167.png)
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Abstract
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In this paper, we propose a novel descriptor called spatially weighted order binary pattern (SWOBP) for color texture classification. The SWOBP descriptor not only encodes color order information in different channels but also encodes color order relationships in the spatial domain. To achieve these goals, we introduce a color gradient channel to complement the traditional color channels and explore a multi-channel color order pattern to jointly encode inter-channel features. Furthermore, we decompose local color differences into spatially weighted binary templates and use them to encode color order information in a local neighborhood. Finally, we aggregate all the encoded features into image histograms as texture descriptor. Experiments on five benchmark databases demonstrate that the proposed SWOBP descriptor achieves the state-of-the-art performance for color texture classification. (C) 2020 Elsevier Ltd. All rights reserved.
Keywords:
Color
Features
Local Binary Pattern (LBP)
Texture classification
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