Using fractal characteristics such as fractal dimension , lacunarity and succolarity to characterize texture patterns on images
Autor(a) principal: | |
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Data de Publicação: | 2007 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional da Universidade Federal Fluminense (RIUFF) |
Texto Completo: | https://app.uff.br/riuff/handle/1/17146 |
Resumo: | Three aspects of texture are considered by the fractal geometry. Fractal Dimension (FD), Lacunarity and Succolarity. Fractal Dimension has been well studied;a great numbers of approaches have been presented to extract it from images. It can be computed from black-white to multi-band image. There are many approaches also, from the simple Box-Dimension to the most complex Hausdorff Dimension. The same does not happen with the other two measures. Although Lacunarity has been more and more used in works exploring its characteristics, Succolarity, until now, has not been computed. This work presents a method to compute Succolarity, as well as a demonstration of its applicability, differences and similarities to each fractal measure. The proposed method for this computation is based on the Box Couting approach adapted to the notions of Succolarity. A simple example is shown step by step to easily explain how to compute the Succolarity for binary images and for 3D objects. Moreover, this work presents a procedure to calculate the Lacunarity of 3D objects. This proposal is organized in a way that it could be used to evaluate also the Lacunarity of grey-scale images in two different manners. The main goal of the work is to show that the Succolarity can be used as a new feature in the pattern recognition process, especially for identification of natural textures. The combination of this measure with fractal dimension and Lacunarity is useful to identity different types of texture on images. |
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Using fractal characteristics such as fractal dimension , lacunarity and succolarity to characterize texture patterns on imagesProcessamento de imagemTécnica digitalDimensão fractalAnálise de textura de imagensImagem 3DFractalSucolaridadeLacunaridade 3DMedidas fractaisAnálise bináriaImagens preto e brancasSuccolarityFractal dimension3D lacunarityFractal measuresBinary image analysisBlack & white imagesCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::TEORIA DA COMPUTACAO::COMPUTABILIDADE E MODELOS DE COMPUTACAOThree aspects of texture are considered by the fractal geometry. Fractal Dimension (FD), Lacunarity and Succolarity. Fractal Dimension has been well studied;a great numbers of approaches have been presented to extract it from images. It can be computed from black-white to multi-band image. There are many approaches also, from the simple Box-Dimension to the most complex Hausdorff Dimension. The same does not happen with the other two measures. Although Lacunarity has been more and more used in works exploring its characteristics, Succolarity, until now, has not been computed. This work presents a method to compute Succolarity, as well as a demonstration of its applicability, differences and similarities to each fractal measure. The proposed method for this computation is based on the Box Couting approach adapted to the notions of Succolarity. A simple example is shown step by step to easily explain how to compute the Succolarity for binary images and for 3D objects. Moreover, this work presents a procedure to calculate the Lacunarity of 3D objects. This proposal is organized in a way that it could be used to evaluate also the Lacunarity of grey-scale images in two different manners. The main goal of the work is to show that the Succolarity can be used as a new feature in the pattern recognition process, especially for identification of natural textures. The combination of this measure with fractal dimension and Lacunarity is useful to identity different types of texture on images.geometria fractal possui três medidas para caracterizar texturas: Dimensão Fractal (FD), Lacunaridade e Sucolaridade. A Dimensão Fractal é a mais conhecida e estudada. É também a que possui mais metodologias para o cálculo por imagens. Pode ser calculada para imagens em preto e branco bem como para imagens de satélite com várias bandas. A FD pode ser avaliada por diversos métodos, desde o simples método do "Box - Dimension" a mais complexa dimensão de Hausdorff. O mesmo não acontece com as duas outras medidas. Embora cada vez mais trabalhos tenham explorado as características da Lacunaridade, a Sucolaridade, até então não tem sido calculada. Este trabalho apresenta um método para calcular a Sucolaridade. Demonstra a sua usabilidade em imagens reais, bem como as semelhanças e diferenças de cada medida fiactal. A proposta de cálculo para esta medida se baseia no método "Box Counting" com adaptações para que este atenda as noções da Sucolaridade. O passo a passo de um exemplo simples explica a forma de cálculo proposta para imagens binárias e para objetos 3D. Além disso, este trabalho apresenta uma abordagem para o cálculo da Lacunaridade de objetos 3D. Esta proposta inclui uma forma de calcular também a Lacunaridade de imagens em tons de cinza de duas formas distintas. O principal objetivo deste trabalho é mostrar que a Sucolaridade pode ser usada como uma nova característica em processos de reconhecimento de padrões, especialmente na identificação de texturas naturais. Além disso, esta medida, combinada com a Dimensão Fractal e a Lacunaridade, é muito útil para identificar diferentes tipos de texturas em imagens.Programa de Pós-Graduação em ComputaçãoComputaçãoConci, AuraCPF:01090879922http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4787952Y2Montenegro, Anselmo AntunesCPF:37768904222http://lattes.cnpq.br/3518240071127311Casas, Estevam Barbosa de LasCPF:41090544322http://lattes.cnpq.br/6740018257272418Melo, Rafael Heitor Correia de2021-03-10T19:09:51Z2008-06-162021-03-10T19:09:51Z2007-08-24info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfapplication/pdfhttps://app.uff.br/riuff/handle/1/17146porCC-BY-SAinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da Universidade Federal Fluminense (RIUFF)instname:Universidade Federal Fluminense (UFF)instacron:UFF2021-03-10T19:09:51Zoai:app.uff.br:1/17146Repositório InstitucionalPUBhttps://app.uff.br/oai/requestriuff@id.uff.bropendoar:21202021-03-10T19:09:51Repositório Institucional da Universidade Federal Fluminense (RIUFF) - Universidade Federal Fluminense (UFF)false |
dc.title.none.fl_str_mv |
Using fractal characteristics such as fractal dimension , lacunarity and succolarity to characterize texture patterns on images |
title |
Using fractal characteristics such as fractal dimension , lacunarity and succolarity to characterize texture patterns on images |
spellingShingle |
Using fractal characteristics such as fractal dimension , lacunarity and succolarity to characterize texture patterns on images Melo, Rafael Heitor Correia de Processamento de imagem Técnica digital Dimensão fractal Análise de textura de imagens Imagem 3D Fractal Sucolaridade Lacunaridade 3D Medidas fractais Análise binária Imagens preto e brancas Succolarity Fractal dimension 3D lacunarity Fractal measures Binary image analysis Black & white images CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::TEORIA DA COMPUTACAO::COMPUTABILIDADE E MODELOS DE COMPUTACAO |
title_short |
Using fractal characteristics such as fractal dimension , lacunarity and succolarity to characterize texture patterns on images |
title_full |
Using fractal characteristics such as fractal dimension , lacunarity and succolarity to characterize texture patterns on images |
title_fullStr |
Using fractal characteristics such as fractal dimension , lacunarity and succolarity to characterize texture patterns on images |
title_full_unstemmed |
Using fractal characteristics such as fractal dimension , lacunarity and succolarity to characterize texture patterns on images |
title_sort |
Using fractal characteristics such as fractal dimension , lacunarity and succolarity to characterize texture patterns on images |
author |
Melo, Rafael Heitor Correia de |
author_facet |
Melo, Rafael Heitor Correia de |
author_role |
author |
dc.contributor.none.fl_str_mv |
Conci, Aura CPF:01090879922 http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4787952Y2 Montenegro, Anselmo Antunes CPF:37768904222 http://lattes.cnpq.br/3518240071127311 Casas, Estevam Barbosa de Las CPF:41090544322 http://lattes.cnpq.br/6740018257272418 |
dc.contributor.author.fl_str_mv |
Melo, Rafael Heitor Correia de |
dc.subject.por.fl_str_mv |
Processamento de imagem Técnica digital Dimensão fractal Análise de textura de imagens Imagem 3D Fractal Sucolaridade Lacunaridade 3D Medidas fractais Análise binária Imagens preto e brancas Succolarity Fractal dimension 3D lacunarity Fractal measures Binary image analysis Black & white images CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::TEORIA DA COMPUTACAO::COMPUTABILIDADE E MODELOS DE COMPUTACAO |
topic |
Processamento de imagem Técnica digital Dimensão fractal Análise de textura de imagens Imagem 3D Fractal Sucolaridade Lacunaridade 3D Medidas fractais Análise binária Imagens preto e brancas Succolarity Fractal dimension 3D lacunarity Fractal measures Binary image analysis Black & white images CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::TEORIA DA COMPUTACAO::COMPUTABILIDADE E MODELOS DE COMPUTACAO |
description |
Three aspects of texture are considered by the fractal geometry. Fractal Dimension (FD), Lacunarity and Succolarity. Fractal Dimension has been well studied;a great numbers of approaches have been presented to extract it from images. It can be computed from black-white to multi-band image. There are many approaches also, from the simple Box-Dimension to the most complex Hausdorff Dimension. The same does not happen with the other two measures. Although Lacunarity has been more and more used in works exploring its characteristics, Succolarity, until now, has not been computed. This work presents a method to compute Succolarity, as well as a demonstration of its applicability, differences and similarities to each fractal measure. The proposed method for this computation is based on the Box Couting approach adapted to the notions of Succolarity. A simple example is shown step by step to easily explain how to compute the Succolarity for binary images and for 3D objects. Moreover, this work presents a procedure to calculate the Lacunarity of 3D objects. This proposal is organized in a way that it could be used to evaluate also the Lacunarity of grey-scale images in two different manners. The main goal of the work is to show that the Succolarity can be used as a new feature in the pattern recognition process, especially for identification of natural textures. The combination of this measure with fractal dimension and Lacunarity is useful to identity different types of texture on images. |
publishDate |
2007 |
dc.date.none.fl_str_mv |
2007-08-24 2008-06-16 2021-03-10T19:09:51Z 2021-03-10T19:09:51Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://app.uff.br/riuff/handle/1/17146 |
url |
https://app.uff.br/riuff/handle/1/17146 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
CC-BY-SA info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
CC-BY-SA |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Programa de Pós-Graduação em Computação Computação |
publisher.none.fl_str_mv |
Programa de Pós-Graduação em Computação Computação |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da Universidade Federal Fluminense (RIUFF) instname:Universidade Federal Fluminense (UFF) instacron:UFF |
instname_str |
Universidade Federal Fluminense (UFF) |
instacron_str |
UFF |
institution |
UFF |
reponame_str |
Repositório Institucional da Universidade Federal Fluminense (RIUFF) |
collection |
Repositório Institucional da Universidade Federal Fluminense (RIUFF) |
repository.name.fl_str_mv |
Repositório Institucional da Universidade Federal Fluminense (RIUFF) - Universidade Federal Fluminense (UFF) |
repository.mail.fl_str_mv |
riuff@id.uff.br |
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1802135372903219200 |