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Open AccessArticle

RGB Inter-Channel Measures for Morphological Color Texture Characterization

1
Facultad Politécnica, Universidad Nacional de Asunción, San Lorenzo 2160, Paraguay
2
Department of Computer Science, Royal Holloway, University of London, Egham TW20 0EX, UK
3
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; https://doi.org/10.3390/sym11101190
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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