Identity statement area
Reference TypeConference Paper (Conference Proceedings)
Last Update2017: (UTC) administrator
Metadata Last Update2021: (UTC) administrator
Citation KeyCondori:2017:ExDiIm
TitleExtending the Differential Image Foresting Transform to Root-based Path-cost Functions with Application to Superpixel Segmentation
Access Date2022, Jan. 24
Number of Files1
Size1587 KiB
Context area
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
Conference NameConference on Graphics, Patterns and Images, 30 (SIBGRAPI)
Conference LocationNiterói, RJ
DateOct. 17-20, 2017
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2017-08-22 02:28:20 :: -> administrator ::
2021-02-23 03:53:12 :: administrator -> :: 2017
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Content TypeExternal Contribution
KeywordsImage Foresting Transform
Differential Image Foresting Transform
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. > SDLA > SIBGRAPI 2017 > Extending the Differential...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 21/08/2017 23:28 1.2 KiB 
Conditions of access and use area
data URL
zipped data URL
Target Filecondori148.pdf
Update Permissionnot transferred
Allied materials area
Next Higher Units8JMKD3MGPAW/3PKCC58
Notes area
Empty Fieldsaccessionnumber archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume