Nonlinear smoothing of skin lesions images driven by derivative filters
Autor(a) principal: | |
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Data de Publicação: | 2010 |
Outros Autores: | , , , |
Tipo de documento: | Livro |
Idioma: | por |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/10216/20493 |
Resumo: | Image segmentation is an important step to suitable extraction of features of objects from images. However, the presence of noise interferes in segmentation quality; for example, by generating the detection of false edges (or false borders). To diminish the problems caused by the presence of noise in images, various smoothing techniques have been proposed to pre-process the original images. Those methods reduce the noise presented in input images, but they can also strongly affect the borders of the objects, leading to the loss of important details, such as the original roughness of the contours or the elimination of the borders of small objects. Among the existing smoothing techniques, one of the most promising is based on the use of anisotropic diffusion, which allows a selective smoothing that decreases the undesirable effects caused by noise presented in the input image and preserves the edges of the objects. However, the success of this smoothing method is strongly reliant on the number of iterations performed that depends on the input image. In this work, we propose the use of derivative filters for the definition of the appropriate number of iterations adopted by the smoothing method based on anisotropic diffusion, when it is applied for the removal of noise usually present in images of skin lesions. The experimental results demonstrate that the developed solution is promising, being able to determine the adequate number of iterations for smoothing the input images avoiding the excessive loss of details of the borders of the lesions presented in images. |
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Nonlinear smoothing of skin lesions images driven by derivative filtersCiências Tecnológicas, Outras ciências da engenharia e tecnologiasTechnological sciences, Other engineering and technologiesImage segmentation is an important step to suitable extraction of features of objects from images. However, the presence of noise interferes in segmentation quality; for example, by generating the detection of false edges (or false borders). To diminish the problems caused by the presence of noise in images, various smoothing techniques have been proposed to pre-process the original images. Those methods reduce the noise presented in input images, but they can also strongly affect the borders of the objects, leading to the loss of important details, such as the original roughness of the contours or the elimination of the borders of small objects. Among the existing smoothing techniques, one of the most promising is based on the use of anisotropic diffusion, which allows a selective smoothing that decreases the undesirable effects caused by noise presented in the input image and preserves the edges of the objects. However, the success of this smoothing method is strongly reliant on the number of iterations performed that depends on the input image. In this work, we propose the use of derivative filters for the definition of the appropriate number of iterations adopted by the smoothing method based on anisotropic diffusion, when it is applied for the removal of noise usually present in images of skin lesions. The experimental results demonstrate that the developed solution is promising, being able to determine the adequate number of iterations for smoothing the input images avoiding the excessive loss of details of the borders of the lesions presented in images.20102010-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/20493porAlex F. AraújoAledir S. PereiraNorian MarranghelloJonathan RogériJoão Manuel R. S. Tavaresinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T14:33:37Zoai:repositorio-aberto.up.pt:10216/20493Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:03:53.962160Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Nonlinear smoothing of skin lesions images driven by derivative filters |
title |
Nonlinear smoothing of skin lesions images driven by derivative filters |
spellingShingle |
Nonlinear smoothing of skin lesions images driven by derivative filters Alex F. Araújo Ciências Tecnológicas, Outras ciências da engenharia e tecnologias Technological sciences, Other engineering and technologies |
title_short |
Nonlinear smoothing of skin lesions images driven by derivative filters |
title_full |
Nonlinear smoothing of skin lesions images driven by derivative filters |
title_fullStr |
Nonlinear smoothing of skin lesions images driven by derivative filters |
title_full_unstemmed |
Nonlinear smoothing of skin lesions images driven by derivative filters |
title_sort |
Nonlinear smoothing of skin lesions images driven by derivative filters |
author |
Alex F. Araújo |
author_facet |
Alex F. Araújo Aledir S. Pereira Norian Marranghello Jonathan Rogéri João Manuel R. S. Tavares |
author_role |
author |
author2 |
Aledir S. Pereira Norian Marranghello Jonathan Rogéri João Manuel R. S. Tavares |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Alex F. Araújo Aledir S. Pereira Norian Marranghello Jonathan Rogéri João Manuel R. S. Tavares |
dc.subject.por.fl_str_mv |
Ciências Tecnológicas, Outras ciências da engenharia e tecnologias Technological sciences, Other engineering and technologies |
topic |
Ciências Tecnológicas, Outras ciências da engenharia e tecnologias Technological sciences, Other engineering and technologies |
description |
Image segmentation is an important step to suitable extraction of features of objects from images. However, the presence of noise interferes in segmentation quality; for example, by generating the detection of false edges (or false borders). To diminish the problems caused by the presence of noise in images, various smoothing techniques have been proposed to pre-process the original images. Those methods reduce the noise presented in input images, but they can also strongly affect the borders of the objects, leading to the loss of important details, such as the original roughness of the contours or the elimination of the borders of small objects. Among the existing smoothing techniques, one of the most promising is based on the use of anisotropic diffusion, which allows a selective smoothing that decreases the undesirable effects caused by noise presented in the input image and preserves the edges of the objects. However, the success of this smoothing method is strongly reliant on the number of iterations performed that depends on the input image. In this work, we propose the use of derivative filters for the definition of the appropriate number of iterations adopted by the smoothing method based on anisotropic diffusion, when it is applied for the removal of noise usually present in images of skin lesions. The experimental results demonstrate that the developed solution is promising, being able to determine the adequate number of iterations for smoothing the input images avoiding the excessive loss of details of the borders of the lesions presented in images. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010 2010-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/book |
format |
book |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10216/20493 |
url |
https://hdl.handle.net/10216/20493 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799135963427897344 |