@InProceedings{VieiraChieFerrGonz:2012:ImMiAn,
author = "Vieira, Raissa Tavares and Chierici, Carlos Eduardo de Oliveira
and Ferraz, Carolina Toledo and Gonzaga, Adilson",
affiliation = "{University of S{\~a}o Paulo} and {University of S{\~a}o Paulo}
and {University of S{\~a}o Paulo} and {University of S{\~a}o
Paulo}",
title = "Image micro-pattern analysis using Fuzzy Numbers",
booktitle = "Proceedings...",
year = "2012",
editor = "Freitas, Carla Maria Dal Sasso and Sarkar, Sudeep and Scopigno,
Roberto and Silva, Luciano",
organization = "Conference on Graphics, Patterns and Images, 25. (SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "micro-pattern analysis, fuzzy numbers, texture analysis.",
abstract = "This paper proposes a new methodology for micropattern analysis in
digital images based on fuzzy numbers. A micro-pattern is the
structure of the gray-level pixels within a neighborhood and can
describe the spatial context of the image, such as edge, line,
spot, blob, corner, texture, and more complex patterns. By
treating a pixel neighborhood as a fuzzy set and each pixel
gray-level as a fuzzy number, we can evaluate the membership
degree of the central pixel to the others. We have called this
method the Local Fuzzy Pattern (LFP). Using a sigmoid membership
function, we proved that the proposed methodology surpasses the
Hit-rate of the Local Binary Pattern (LBP), for texture
classification. The LFP proved to be robust to image rotation.
Moreover, our proposed formulation for the LFP is a generalization
of previously published techniques, such as Texture Unit, LBP,
FUNED, and Census Transform.",
conference-location = "Ouro Preto",
conference-year = "Aug. 22-25, 2012",
language = "en",
targetfile = "Image micro-pattern analysis using Fuzzy Numbers.pdf",
urlaccessdate = "2021, Jan. 24"
}