The weighted gradient: a color image gradient applied to morphological segmentation
Autor(a) principal: | |
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Data de Publicação: | 2006 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Journal of the Brazilian Computer Society |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002006000100005 |
Resumo: | This paper proposes a method for color gradient computation applied to morphological segmentation of color images. The weighted gradient (with weights estimated automatically), proposed in this paper, applied in conjunction with the watershed from markers technique, provides excelent segmentation results, according to a subjective visual criterion. The weighted gradient is computed by linear combination of the gradients from each band of an image under the IHS color space model. The weights to each gradient are estimated by a systematic method that computes the similarity between the image to compute the gradient and an "ideal image", whose histogram has an uniform distribution. Several experiments were done in order to compare the segmentation results provided by the weighted gradient to the results provided by other color space metrics, also according to a subjective criterion, and such comparison is present in this paper. |
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oai:scielo:S0104-65002006000100005 |
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UFRGS-28 |
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Journal of the Brazilian Computer Society |
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The weighted gradient: a color image gradient applied to morphological segmentationWeighted GradientColor GradientMorphological SegmentationWatershed from MarkersBray-Curtis Distance FunctionWeight EstimationThis paper proposes a method for color gradient computation applied to morphological segmentation of color images. The weighted gradient (with weights estimated automatically), proposed in this paper, applied in conjunction with the watershed from markers technique, provides excelent segmentation results, according to a subjective visual criterion. The weighted gradient is computed by linear combination of the gradients from each band of an image under the IHS color space model. The weights to each gradient are estimated by a systematic method that computes the similarity between the image to compute the gradient and an "ideal image", whose histogram has an uniform distribution. Several experiments were done in order to compare the segmentation results provided by the weighted gradient to the results provided by other color space metrics, also according to a subjective criterion, and such comparison is present in this paper.Sociedade Brasileira de Computação2006-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002006000100005Journal of the Brazilian Computer Society v.11 n.3 2006reponame:Journal of the Brazilian Computer Societyinstname:Sociedade Brasileira de Computação (SBC)instacron:UFRGS10.1007/BF03192382info:eu-repo/semantics/openAccessFlores,Franklin CésarPolidório,Airton MarcoLotufo,Roberto de Alencareng2010-10-26T00:00:00Zoai:scielo:S0104-65002006000100005Revistahttps://journal-bcs.springeropen.com/PUBhttps://old.scielo.br/oai/scielo-oai.phpjbcs@icmc.sc.usp.br1678-48040104-6500opendoar:2010-10-26T00:00Journal of the Brazilian Computer Society - Sociedade Brasileira de Computação (SBC)false |
dc.title.none.fl_str_mv |
The weighted gradient: a color image gradient applied to morphological segmentation |
title |
The weighted gradient: a color image gradient applied to morphological segmentation |
spellingShingle |
The weighted gradient: a color image gradient applied to morphological segmentation Flores,Franklin César Weighted Gradient Color Gradient Morphological Segmentation Watershed from Markers Bray-Curtis Distance Function Weight Estimation |
title_short |
The weighted gradient: a color image gradient applied to morphological segmentation |
title_full |
The weighted gradient: a color image gradient applied to morphological segmentation |
title_fullStr |
The weighted gradient: a color image gradient applied to morphological segmentation |
title_full_unstemmed |
The weighted gradient: a color image gradient applied to morphological segmentation |
title_sort |
The weighted gradient: a color image gradient applied to morphological segmentation |
author |
Flores,Franklin César |
author_facet |
Flores,Franklin César Polidório,Airton Marco Lotufo,Roberto de Alencar |
author_role |
author |
author2 |
Polidório,Airton Marco Lotufo,Roberto de Alencar |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Flores,Franklin César Polidório,Airton Marco Lotufo,Roberto de Alencar |
dc.subject.por.fl_str_mv |
Weighted Gradient Color Gradient Morphological Segmentation Watershed from Markers Bray-Curtis Distance Function Weight Estimation |
topic |
Weighted Gradient Color Gradient Morphological Segmentation Watershed from Markers Bray-Curtis Distance Function Weight Estimation |
description |
This paper proposes a method for color gradient computation applied to morphological segmentation of color images. The weighted gradient (with weights estimated automatically), proposed in this paper, applied in conjunction with the watershed from markers technique, provides excelent segmentation results, according to a subjective visual criterion. The weighted gradient is computed by linear combination of the gradients from each band of an image under the IHS color space model. The weights to each gradient are estimated by a systematic method that computes the similarity between the image to compute the gradient and an "ideal image", whose histogram has an uniform distribution. Several experiments were done in order to compare the segmentation results provided by the weighted gradient to the results provided by other color space metrics, also according to a subjective criterion, and such comparison is present in this paper. |
publishDate |
2006 |
dc.date.none.fl_str_mv |
2006-04-01 |
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=S0104-65002006000100005 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-65002006000100005 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1007/BF03192382 |
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 |
Sociedade Brasileira de Computação |
publisher.none.fl_str_mv |
Sociedade Brasileira de Computação |
dc.source.none.fl_str_mv |
Journal of the Brazilian Computer Society v.11 n.3 2006 reponame:Journal of the Brazilian Computer Society instname:Sociedade Brasileira de Computação (SBC) instacron:UFRGS |
instname_str |
Sociedade Brasileira de Computação (SBC) |
instacron_str |
UFRGS |
institution |
UFRGS |
reponame_str |
Journal of the Brazilian Computer Society |
collection |
Journal of the Brazilian Computer Society |
repository.name.fl_str_mv |
Journal of the Brazilian Computer Society - Sociedade Brasileira de Computação (SBC) |
repository.mail.fl_str_mv |
jbcs@icmc.sc.usp.br |
_version_ |
1754734669908148224 |