Compact Color Texture Representation by Feature Selection in Multiple Color Spaces

M. Alimoussa; N. Vandenbroucke; A. Porebski; R. Oulad Haj Thami; S. El Fkihi; D. Hamad

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Paper

Compact Color Texture Representation by Feature Selection in Multiple Color Spaces

Topics: Color and Texture Analyses; Features Extraction

In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP, 436-443, 2019 , Prague, Czech Republic

Authors: M. Alimoussa ¹ ; N. Vandenbroucke ² ; A. Porebski ² ; R. Oulad Haj Thami ¹ ; S. El Fkihi ¹ and D. Hamad ²

Affiliations: ¹ Advanced Digital Entreprise Modeling and Information Retrieval Laboratory, ENSIAS, Rabat and Morocco ; ² Laboratoire d’Informatique Signal et Image de la Côte d’Opale, 62228 Calais and France

Keyword(s): Color Texture Classification, Feature Selection, Color LBP Histogram, Chromatic Cooccurrence Matrix.

Related Ontology Subjects/Areas/Topics: Color and Texture Analyses ; Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis

Abstract: This paper presents a compact color texture representation based on the selection of features extracted from different configurations of descriptors computed in multiple color spaces. The proposed representation aims to take simultaneously into account several spatial and color properties of different textures. For this purpose, texture images are coded in five different color spaces. Then, texture descriptors with different neighborhood and quantization parameter settings, are calculated from this images in order to extract a high dimensionality feature vector describing the textures. Compact representation is finally obtained by means of a feature selection scheme. Our approach is applied with two well-known color texture descriptors for the classification of three benchmark image databases.

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Paper citation in several formats:

Alimoussa, M.; Vandenbroucke, N.; Porebski, A.; Thami, R.; El Fkihi, S. and Hamad, D. (2019). Compact Color Texture Representation by Feature Selection in Multiple Color Spaces. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP; ISBN 978-989-758-354-4; ISSN 2184-4321, SciTePress, pages 436-443. DOI: 10.5220/0007578704360443

@conference{visapp19,
author={M. Alimoussa. and N. Vandenbroucke. and A. Porebski. and R. Oulad Haj Thami. and S. {El Fkihi}. and D. Hamad.},
title={Compact Color Texture Representation by Feature Selection in Multiple Color Spaces},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP},
year={2019},
pages={436-443},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007578704360443},
isbn={978-989-758-354-4},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP
TI - Compact Color Texture Representation by Feature Selection in Multiple Color Spaces
SN - 978-989-758-354-4
IS - 2184-4321
AU - Alimoussa, M.
AU - Vandenbroucke, N.
AU - Porebski, A.
AU - Thami, R.
AU - El Fkihi, S.
AU - Hamad, D.
PY - 2019
SP - 436
EP - 443
DO - 10.5220/0007578704360443
PB - SciTePress