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Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPAW/3PFS8RS
Repositorysid.inpe.br/sibgrapi/2017/08.22.02.28
Last Update2017:08.22.02.28.20 administrator
Metadatasid.inpe.br/sibgrapi/2017/08.22.02.28.20
Metadata Last Update2020:02.19.02.01.41 administrator
Citation KeyCondori:2017:ExDiIm
TitleExtending the Differential Image Foresting Transform to Root-based Path-cost Functions with Application to Superpixel Segmentation
FormatOn-line
Year2017
Access Date2021, Jan. 26
Number of Files1
Size1587 KiB
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AuthorCondori, Marcos Ademir Tejada
AffiliationUniversity of Sao Paulo, Institute of Mathematics and Statistics, Sao Paulo, SP, Brazil
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
e-Mail Addressmarcostejadac@gmail.com
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ
DateOct. 17-20, 2017
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2017-08-22 02:28:20 :: marcostejadac@gmail.com -> administrator ::
2020-02-19 02:01:41 :: administrator -> :: 2017
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Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
KeywordsImage Foresting Transform, Superpixels, Differential Image Foresting Transform, IFT-SLIC.
AbstractThe Image Foresting Transform (IFT) is a general framework to develop image processing tools for a variety of tasks such as image segmentation, boundary tracking, morphological filters, pixel clustering, among others. The Differential Image Foresting Transform (DIFT) comes in handy for scenarios where multiple iterations of IFT over the same image with small modifications on the input parameters are expected, reducing the processing complexity from linear to sublinear with respect to the number of pixels. In this paper, we propose an enhanced variant of the DIFT algorithm that avoids inconsistencies, when the connectivity function is not monotonically incremental. Our algorithm works with the classical and non-classifical connectivity functions based on root position. Experiments were conducted on a superpixel task, showing a significant improvement to a state-of-the-art method.
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data URLhttp://urlib.net/rep/8JMKD3MGPAW/3PFS8RS
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3PFS8RS
Languageen
Target Filecondori148.pdf
User Groupmarcostejadac@gmail.com
Visibilityshown
Update Permissionnot transferred
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Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3PJT9LS
8JMKD3MGPAW/3PKCC58
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
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