Classification of color textures with random field models and neural networks

A number of texture classification approaches have been developed in the past but most of these studies target graylevel textures. In this work, novel results are presented on Neural Network based classification of color textures in a very large heterogeneous database. Several different Multispectra...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Hernandez, Orlando J., Cook, John, Griffin, Michael, De Rama, Cynthia, McGovern, Michael
Formato: Articulo
Lenguaje:Inglés
Publicado: 2005
Materias:
Ciencias Informáticas
Color, shading, shadowing, and texture
Neural nets
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/9587
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct05-6.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-9587
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Color, shading, shadowing, and texture
Neural nets
spellingShingle Ciencias Informáticas
Color, shading, shadowing, and texture
Neural nets
Hernandez, Orlando J.
Cook, John
Griffin, Michael
De Rama, Cynthia
McGovern, Michael
Classification of color textures with random field models and neural networks
topic_facet Ciencias Informáticas
Color, shading, shadowing, and texture
Neural nets
description A number of texture classification approaches have been developed in the past but most of these studies target graylevel textures. In this work, novel results are presented on Neural Network based classification of color textures in a very large heterogeneous database. Several different Multispectral Random Field models are used to characterize the textures. The classifying features are based on the estimated parameters of these model and functions defined on them. The approach is tested on a database of 73 different color textures classes. The advantage of utilizing color information is demonstrated by converting color textures to gray-level ones and classifying them using Grey Level Co-Occurrence Matrix (GLCM) based features.
format Articulo
Articulo
author Hernandez, Orlando J.
Cook, John
Griffin, Michael
De Rama, Cynthia
McGovern, Michael
author_facet Hernandez, Orlando J.
Cook, John
Griffin, Michael
De Rama, Cynthia
McGovern, Michael
author_sort Hernandez, Orlando J.
title Classification of color textures with random field models and neural networks
title_short Classification of color textures with random field models and neural networks
title_full Classification of color textures with random field models and neural networks
title_fullStr Classification of color textures with random field models and neural networks
title_full_unstemmed Classification of color textures with random field models and neural networks
title_sort classification of color textures with random field models and neural networks
publishDate 2005
url http://sedici.unlp.edu.ar/handle/10915/9587
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct05-6.pdf
work_keys_str_mv AT hernandezorlandoj classificationofcolortextureswithrandomfieldmodelsandneuralnetworks
AT cookjohn classificationofcolortextureswithrandomfieldmodelsandneuralnetworks
AT griffinmichael classificationofcolortextureswithrandomfieldmodelsandneuralnetworks
AT deramacynthia classificationofcolortextureswithrandomfieldmodelsandneuralnetworks
AT mcgovernmichael classificationofcolortextureswithrandomfieldmodelsandneuralnetworks
bdutipo_str Repositorios
_version_ 1764820493306691586

Ejemplares similares