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Open AccessArticle

RGB Inter-Channel Measures for Morphological Color Texture Characterization

Facultad Politécnica, Universidad Nacional de Asunción, San Lorenzo 2160, Paraguay
Department of Computer Science, Royal Holloway, University of London, Egham TW20 0EX, UK
Division of Computer Science, Universidad Pablo de Olavide, ES-41013 Seville, Spain
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Symmetry 2019, 11(10), 1190;
Received: 3 September 2019 / Revised: 15 September 2019 / Accepted: 18 September 2019 / Published: 20 September 2019
The perception of textures is based on high-level features such as symmetry, brightness, color or direction. Texture characterization is a widely studied topic in the image processing community. The normalized volume of morphological series is used as a texture descriptor in RGB images. However, the correlation between different color channels is not exploited with this descriptor. We propose the usage of inter-channel measures in addition to the volume, to enhance the descriptors potential to discriminate textures. The experiments show that standard texture classification techniques increase between 3%–10% in performance when using our descriptor instead of other state of the art descriptors that do not use inter-channel measures. View Full-Text
Keywords: feature extraction; texture characterization; mathematical morphology feature extraction; texture characterization; mathematical morphology
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Durañona Sosa, N.L.; Vázquez Noguera, J.L.; Cáceres Silva, J.J.; García Torres, M.; Legal-Ayala, H. RGB Inter-Channel Measures for Morphological Color Texture Characterization. Symmetry 2019, 11, 1190.

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