Color image segmentation using multispectral random field texture model & color content features
- Autores
- Hernandez, Orlando J.; Khotanzad, Alireza
- Año de publicación
- 2004
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- This paper describes a color texture-based image segmentation system. The color texture information is obtained via modeling with the Multispectral Simultaneous Auto Regressive (MSAR) random field model. The general color content characterized by ratios of sample color means is also used. The image is segmented into regions of uniform color texture using an unsupervised histogram clustering approach that utilizes the combination of MSAR and color features. The performance of the system is tested on two databases containing synthetic mosaics of natural textures and natural scenes, respectively
Facultad de Informática - Materia
-
Ciencias Informáticas
Color, shading, shadowing, and texture
Segmentation - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc/3.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/9495
Ver los metadatos del registro completo
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Color image segmentation using multispectral random field texture model & color content featuresHernandez, Orlando J.Khotanzad, AlirezaCiencias InformáticasColor, shading, shadowing, and textureSegmentationThis paper describes a color texture-based image segmentation system. The color texture information is obtained via modeling with the Multispectral Simultaneous Auto Regressive (MSAR) random field model. The general color content characterized by ratios of sample color means is also used. The image is segmented into regions of uniform color texture using an unsupervised histogram clustering approach that utilizes the combination of MSAR and color features. The performance of the system is tested on two databases containing synthetic mosaics of natural textures and natural scenes, respectivelyFacultad de Informática2004-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf141-146http://sedici.unlp.edu.ar/handle/10915/9495enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct04-3.pdfinfo:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/3.0/Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:50:44Zoai:sedici.unlp.edu.ar:10915/9495Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:50:44.201SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Color image segmentation using multispectral random field texture model & color content features |
title |
Color image segmentation using multispectral random field texture model & color content features |
spellingShingle |
Color image segmentation using multispectral random field texture model & color content features Hernandez, Orlando J. Ciencias Informáticas Color, shading, shadowing, and texture Segmentation |
title_short |
Color image segmentation using multispectral random field texture model & color content features |
title_full |
Color image segmentation using multispectral random field texture model & color content features |
title_fullStr |
Color image segmentation using multispectral random field texture model & color content features |
title_full_unstemmed |
Color image segmentation using multispectral random field texture model & color content features |
title_sort |
Color image segmentation using multispectral random field texture model & color content features |
dc.creator.none.fl_str_mv |
Hernandez, Orlando J. Khotanzad, Alireza |
author |
Hernandez, Orlando J. |
author_facet |
Hernandez, Orlando J. Khotanzad, Alireza |
author_role |
author |
author2 |
Khotanzad, Alireza |
author2_role |
author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas Color, shading, shadowing, and texture Segmentation |
topic |
Ciencias Informáticas Color, shading, shadowing, and texture Segmentation |
dc.description.none.fl_txt_mv |
This paper describes a color texture-based image segmentation system. The color texture information is obtained via modeling with the Multispectral Simultaneous Auto Regressive (MSAR) random field model. The general color content characterized by ratios of sample color means is also used. The image is segmented into regions of uniform color texture using an unsupervised histogram clustering approach that utilizes the combination of MSAR and color features. The performance of the system is tested on two databases containing synthetic mosaics of natural textures and natural scenes, respectively Facultad de Informática |
description |
This paper describes a color texture-based image segmentation system. The color texture information is obtained via modeling with the Multispectral Simultaneous Auto Regressive (MSAR) random field model. The general color content characterized by ratios of sample color means is also used. The image is segmented into regions of uniform color texture using an unsupervised histogram clustering approach that utilizes the combination of MSAR and color features. The performance of the system is tested on two databases containing synthetic mosaics of natural textures and natural scenes, respectively |
publishDate |
2004 |
dc.date.none.fl_str_mv |
2004-10 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Articulo http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/9495 |
url |
http://sedici.unlp.edu.ar/handle/10915/9495 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct04-3.pdf info:eu-repo/semantics/altIdentifier/issn/1666-6038 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc/3.0/ Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc/3.0/ Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) |
dc.format.none.fl_str_mv |
application/pdf 141-146 |
dc.source.none.fl_str_mv |
reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
reponame_str |
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SEDICI (UNLP) |
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Universidad Nacional de La Plata |
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repository.name.fl_str_mv |
SEDICI (UNLP) - Universidad Nacional de La Plata |
repository.mail.fl_str_mv |
alira@sedici.unlp.edu.ar |
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score |
13.070432 |