@InProceedings{CavalinOliv:2017:ReTeCl,
author = "Cavalin, Paulo and Oliveira, Luiz S.",
affiliation = "{IBM Research} and {Universidade Federal do Paran{\'a} - UFPR}",
title = "A Review of Texture Classification Methods and Databases",
booktitle = "Proceedings...",
year = "2017",
editor = "Torchelsen, Rafael Piccin and Nascimento, Erickson Rangel do and
Panozzo, Daniele and Liu, Zicheng and Farias, Myl{\`e}ne and
Viera, Thales and Sacht, Leonardo and Ferreira, Nivan and Comba,
Jo{\~a}o Luiz Dihl and Hirata, Nina and Schiavon Porto, Marcelo
and Vital, Creto and Pagot, Christian Azambuja and Petronetto,
Fabiano and Clua, Esteban and Cardeal, Fl{\'a}vio",
organization = "Conference on Graphics, Patterns and Images, 30. (SIBGRAPI)",
publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
address = "Porto Alegre",
keywords = "Texture recognition, Image recognition, Deep Learn- ing.",
abstract = "In this survey, we present a review of methods and resources for
texture recognition, presenting the most common techniques that
have been used in the recent decades, along with current
tendencies. That said, this paper covers since the most
traditional approaches, for instance texture descriptors such as
gray-level co-occurence matrices (GLCM) and Local Binary Patterns
(LBP), to more recent approaches such as Convolutional Neural
Networks (CNN) and multi-scale patch-based recognition based on
encoding approaches such as Fisher Vectors. In addition, we point
out relevant references for benchmark datasets, which can help the
reader develop and evaluate new methods.",
conference-location = "Niter{\'o}i, RJ, Brazil",
conference-year = "17-20 Oct. 2017",
language = "en",
ibi = "8JMKD3MGPAW/3PJSQNL",
url = "http://urlib.net/ibi/8JMKD3MGPAW/3PJSQNL",
targetfile = "sibgrapi_paper2017.pdf",
urlaccessdate = "2024, Apr. 27"
}