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Color image segmentation using multispectral random field texture model & color content features

Hernandez, Orlando J. et al · SEDICI UNLP · 2004

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Author / responsible party
Hernandez, Orlando J. et al
Publisher
SEDICI UNLP
Year
2004
Language
English

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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

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APA 7

Hernandez, O. J. E. A. (2004). Color image segmentation using multispectral random field texture model & color content features. http://sedici.unlp.edu.ar/handle/10915/9495

MLA

Hernandez, Orlando J. et al. "Color image segmentation using multispectral random field texture model & color content features." 2004. http://sedici.unlp.edu.ar/handle/10915/9495.

Chicago

Hernandez, Orlando J. et al. 2004. "Color image segmentation using multispectral random field texture model & color content features.". http://sedici.unlp.edu.ar/handle/10915/9495.

Harvard

Hernandez, O. J. E. A. 2004, Color image segmentation using multispectral random field texture model & color content features, SEDICI UNLP, available at: http://sedici.unlp.edu.ar/handle/10915/9495 [Accessed 7 Aug. 2026].

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Title
Color image segmentation using multispectral random field texture model & color content features
Author / contributors
Hernandez, Orlando J. et al
Publisher
SEDICI UNLP
Publication year
2004
Language
English

Subjects

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Ciencias Informáticas; Color shading shadowing and texture; Segmentation
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