@InProceedings{MagalhãesQueiCabr:2018:ClTeUs,
author = "Magalh{\~a}es, Whendell Feij{\'o} and Queiroz, Fabiane da Silva
and Cabral, Raquel da Silva",
affiliation = "{Universidade Federal de Alagoas - Campus Arapiraca} and
{Universidade Federal de Alagoas - Centro de Ci{\^e}ncias
Agr{\'a}rias} and {Universidade Federal de Alagoas - Campus
Arapiraca}",
title = "Classifica{\c{c}}{\~a}o de texturas usando a m{\'e}trica de
centralidade closeness",
booktitle = "Proceedings...",
year = "2018",
editor = "Ross, Arun and Gastal, Eduardo S. L. and Jorge, Joaquim A. and
Queiroz, Ricardo L. de and Minetto, Rodrigo and Sarkar, Sudeep and
Papa, Jo{\~a}o Paulo and Oliveira, Manuel M. and Arbel{\'a}ez,
Pablo and Mery, Domingo and Oliveira, Maria Cristina Ferreira de
and Spina, Thiago Vallin and Mendes, Caroline Mazetto and Costa,
Henrique S{\'e}rgio Gutierrez and Mejail, Marta Estela and Geus,
Klaus de and Scheer, Sergio",
organization = "Conference on Graphics, Patterns and Images, 31. (SIBGRAPI)",
publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
address = "Porto Alegre",
keywords = "redes complexas, classifica{\c{c}}{\~a}o de texturas,
centralidade closeness.",
abstract = "In this paper, we propose a method for automatic description and
classification of image texture. The images are modeled as
weighted directed graphs. We use the centrality measure closeness
and in-degree to generate a feature vector that describes the
texture information. To validate the method, we train a k- Nearest
Neighbors classifier and compare the obtained results with the
Co-occurrence Matrix and Local Binary Patterns texture description
techniques. For the experiments, we use the public dataset,
KTH-TIPS. The accuracy of the proposed method is 95,52% that
overcome the compared techniques.",
conference-location = "Foz do Igua{\c{c}}u, PR, Brazil",
conference-year = "29 Oct.-1 Nov. 2018",
language = "pt",
ibi = "8JMKD3MGPAW/3S49SBP",
url = "http://urlib.net/ibi/8JMKD3MGPAW/3S49SBP",
targetfile = "Classifica{\c{c}}{\~a}o de Texturas Usando a M{\'e}trica de
Centralidade Closeness.pdf",
urlaccessdate = "2024, Apr. 30"
}