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Reference TypeConference Paper (Conference Proceedings)
Last Update2017: (UTC)
Metadata Last Update2020: (UTC) administrator
Citation KeyMoraesBrazVech:2017:ImSeIm
TitleImage Segmentation by Image Foresting Transform with Geodesic Band Constraints
Access Date2022, Jan. 21
Number of Files1
Size4959 KiB
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Author1 de Moraes Braz, Caio
2 Vechiatto de Miranda, Paulo André
Affiliation1 IME-USP
EditorTorchelsen, Rafael Piccin
Nascimento, Erickson Rangel do
Panozzo, Daniele
Liu, Zicheng
Farias, Mylène
Viera, Thales
Sacht, Leonardo
Ferreira, Nivan
Comba, João Luiz Dihl
Hirata, Nina
Schiavon Porto, Marcelo
Vital, Creto
Pagot, Christian Azambuja
Petronetto, Fabiano
Clua, Esteban
Cardeal, Flávio
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ
DateOct. 17-20, 2017
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeMaster's or Doctoral Work
History (UTC)2017-09-11 19:41:10 :: -> administrator ::
2020-02-20 22:06:48 :: administrator -> :: 2017
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Is the master or a copy?is the master
Content Stagecompleted
KeywordsImage Segmentation
shape constraints
AbstractThe Image Foresting Transform framework (IFT) was successfully used to implement several segmentation meth- ods, including watersheds and fuzzy connectedness, however the lack of regularization terms in its formulation leads to a potential irregular (jagged) segmentation. An attempt to avoid this issue is to employ shape constraints that favor more regular shapes. We present a novel shape constraint, called the Geodesic Band Constraint (GBC) and show how it can be efficiently incorporated in the Image Foresting Transform framework, with its proof of optimality in terms of an energy function, subject to the new constraint. This constraint helps us to improve the segmentation of regular objects. The GBC can be also used with a prior shape template in order to drive the segmentation towards a specific shape with a single parameter that controls the degrees of freedom of the allowed deformations subject to the model. > SDLA > SIBGRAPI 2017 > Image Segmentation by...
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