An attribute-based image segmentation method
Autor(a) principal: | |
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Data de Publicação: | 1999 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Materials research (São Carlos. Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-14391999000300006 |
Resumo: | This work addresses a new image segmentation method founded on Digital Topology and Mathematical Morphology grounds. The ABA (attribute based absorptions) transform can be viewed as a region-growing method by flooding simulation working at the scale of the main structures of the image. In this method, the gray level image is treated as a relief flooded from all its local minima, which are progressively detected and merged as the flooding takes place. Each local minimum is exclusively associated to one catchment basin (CB). The CBs merging process is guided by their geometric parameters as depth, area and/or volume. This solution enables the direct segmentation of the original image without the need of a preprocessing step or the explicit marker extraction step, often required by other flooding simulation methods. Some examples of image segmentation, employing the ABA transform, are illustrated for uranium oxide samples. It is shown that the ABA transform presents very good segmentation results even in presence of noisy images. Moreover, it's use is often easier and faster when compared to similar image segmentation methods. |
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Materials research (São Carlos. Online) |
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An attribute-based image segmentation methodimage analysisimage segmentationdigital topologyThis work addresses a new image segmentation method founded on Digital Topology and Mathematical Morphology grounds. The ABA (attribute based absorptions) transform can be viewed as a region-growing method by flooding simulation working at the scale of the main structures of the image. In this method, the gray level image is treated as a relief flooded from all its local minima, which are progressively detected and merged as the flooding takes place. Each local minimum is exclusively associated to one catchment basin (CB). The CBs merging process is guided by their geometric parameters as depth, area and/or volume. This solution enables the direct segmentation of the original image without the need of a preprocessing step or the explicit marker extraction step, often required by other flooding simulation methods. Some examples of image segmentation, employing the ABA transform, are illustrated for uranium oxide samples. It is shown that the ABA transform presents very good segmentation results even in presence of noisy images. Moreover, it's use is often easier and faster when compared to similar image segmentation methods.ABM, ABC, ABPol1999-07-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-14391999000300006Materials Research v.2 n.3 1999reponame:Materials research (São Carlos. Online)instname:Universidade Federal de São Carlos (UFSCAR)instacron:ABM ABC ABPOL10.1590/S1516-14391999000300006info:eu-repo/semantics/openAccessAndrade,M.C. deBertrand,G.Araújo,A.A. deeng2000-01-21T00:00:00Zoai:scielo:S1516-14391999000300006Revistahttp://www.scielo.br/mrPUBhttps://old.scielo.br/oai/scielo-oai.phpdedz@power.ufscar.br1980-53731516-1439opendoar:2000-01-21T00:00Materials research (São Carlos. Online) - Universidade Federal de São Carlos (UFSCAR)false |
dc.title.none.fl_str_mv |
An attribute-based image segmentation method |
title |
An attribute-based image segmentation method |
spellingShingle |
An attribute-based image segmentation method Andrade,M.C. de image analysis image segmentation digital topology |
title_short |
An attribute-based image segmentation method |
title_full |
An attribute-based image segmentation method |
title_fullStr |
An attribute-based image segmentation method |
title_full_unstemmed |
An attribute-based image segmentation method |
title_sort |
An attribute-based image segmentation method |
author |
Andrade,M.C. de |
author_facet |
Andrade,M.C. de Bertrand,G. Araújo,A.A. de |
author_role |
author |
author2 |
Bertrand,G. Araújo,A.A. de |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Andrade,M.C. de Bertrand,G. Araújo,A.A. de |
dc.subject.por.fl_str_mv |
image analysis image segmentation digital topology |
topic |
image analysis image segmentation digital topology |
description |
This work addresses a new image segmentation method founded on Digital Topology and Mathematical Morphology grounds. The ABA (attribute based absorptions) transform can be viewed as a region-growing method by flooding simulation working at the scale of the main structures of the image. In this method, the gray level image is treated as a relief flooded from all its local minima, which are progressively detected and merged as the flooding takes place. Each local minimum is exclusively associated to one catchment basin (CB). The CBs merging process is guided by their geometric parameters as depth, area and/or volume. This solution enables the direct segmentation of the original image without the need of a preprocessing step or the explicit marker extraction step, often required by other flooding simulation methods. Some examples of image segmentation, employing the ABA transform, are illustrated for uranium oxide samples. It is shown that the ABA transform presents very good segmentation results even in presence of noisy images. Moreover, it's use is often easier and faster when compared to similar image segmentation methods. |
publishDate |
1999 |
dc.date.none.fl_str_mv |
1999-07-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-14391999000300006 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-14391999000300006 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S1516-14391999000300006 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
ABM, ABC, ABPol |
publisher.none.fl_str_mv |
ABM, ABC, ABPol |
dc.source.none.fl_str_mv |
Materials Research v.2 n.3 1999 reponame:Materials research (São Carlos. Online) instname:Universidade Federal de São Carlos (UFSCAR) instacron:ABM ABC ABPOL |
instname_str |
Universidade Federal de São Carlos (UFSCAR) |
instacron_str |
ABM ABC ABPOL |
institution |
ABM ABC ABPOL |
reponame_str |
Materials research (São Carlos. Online) |
collection |
Materials research (São Carlos. Online) |
repository.name.fl_str_mv |
Materials research (São Carlos. Online) - Universidade Federal de São Carlos (UFSCAR) |
repository.mail.fl_str_mv |
dedz@power.ufscar.br |
_version_ |
1754212656548413440 |