Web of Science: 2 cites, Scopus: 2 cites, Google Scholar: cites
Enhancing spatio-chromatic representation with more-than-three color coding for image description
Rafegas Fonoll, Ivet (Centre de Visió per Computador (Bellaterra, Catalunya))
Vázquez Corral, Javier (Universitat Pompeu Fabra. Departament de Tecnologies de la Informació i les Comunicacions)
Benavente i Vidal, Robert (Universitat Autònoma de Barcelona. Departament de Ciències de la Computació)
Vanrell i Martorell, Maria Isabel (Universitat Autònoma de Barcelona. Departament de Ciències de la Computació)
Álvarez Fernandez, Susana (Universitat Rovira i Virgili. Departament d'Enginyeria Informàtica i Matemàtiques)

Data: 2017
Resum: The extraction of spatio-chromatic features from color images is usually performed independently on each color channel. Usual 3D color spaces, such as RGB, present a high inter-channel correlation for natural images. This correlation can be reduced using color-opponent representations, but the spatial structure of regions with small color differences is not fully captured in two generic Red-Green and Blue-Yellow channels. To overcome these problems, we propose new color coding that is adapted to the specific content of each image. Our proposal is based on two steps: (a) setting the number of channels to the number of distinctive colors we find in each image (avoiding the problem of channel correlation), and (b) building a channel representation that maximizes contrast differences within each color channel (avoiding the problem of low local contrast). We call this approach more-than-three color coding (MTT) to emphasize the fact that the number of channels is adapted to the image content. The higher the color complexity of an image, the more channels can be used to represent it. Here we select distinctive colors as the most predominant in the image, which we call color pivots, and we build the new color coding strategy using these color pivots as a basis. To evaluate the proposed approach, we measure the efficiency in an image categorization task. We show how a generic descriptor improves performance at the description level when applied to the MTT coding.
Ajuts: European Commission 306337
Ministerio de Economía y Competitividad TIN2015-71537-P
Ministerio de Economía y Competitividad TIN2014-61068-R
Ministerio de Economía y Competitividad IJCI-2014-19516
Drets: Tots els drets reservats.
Llengua: Anglès
Document: Article ; recerca ; Versió acceptada per publicar
Matèria: Color ; Color difference ; Color spaces ; Machine vision ; Visible light ; Visual system
Publicat a: Journal of the Optical Society of America. Optics, image science, and vision, Vol. 34, Num. 5 (May 2017) , p. 827-837, ISSN 1084-7529

DOI: 10.1364/JOSAA.34.000827

19 p, 3.1 MB

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 Registre creat el 2018-11-28, darrera modificació el 2024-05-02

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