Identity statement area
Reference TypeConference Paper (Conference Proceedings)
Last Update2010:
Metadata Last Update2010:
Citation KeyMirandaFalcRupp:2010:HoCoAn
TitleHow to complete any segmentation process interactively via Image Foresting Transform
FormatPrinted, On-line.
Access Date2021, Jan. 27
Number of Files1
Size188 KiB
Context area
Author1 Miranda, Paulo André Vechiatto
2 Falcão, Alexandre Xavier
3 Ruppert, Guilherme Cesar Soares
Affiliation1 Institute of Computing - Unicamp -- CP 6176, 13084-971, Campinas, SP, Brazil
2 Institute of Computing - Unicamp -- CP 6176, 13084-971, Campinas, SP, Brazil
3 Institute of Computing - Unicamp -- CP 6176, 13084-971, Campinas, SP, Brazil
EditorBellon, Olga
Esperança, Claudio
Conference NameConference on Graphics, Patterns and Images, 23 (SIBGRAPI)
Conference LocationGramado
DateAug. 30 - Sep. 3, 2010
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2010-10-01 04:19:39 :: -> :: 2010
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Content TypeExternal Contribution
Keywordsimage foresting transform, robustness in image segmentation, graph search algorithms.
AbstractThe segmentation of poorly defined structures in medical imaging and heterogeneous objects in natural images usually call for considerable user assistance. Consequently, automatic results are often far from desirable and interactive repairs become an essential feature to consider. However, how to import automatic results obtained from external processes and complete their segmentation interactively is an issue, since different tools are based on different optimization criteria. Another simpler related problem concerns how to continue a previous segmentation obtained by the same interactive tool. This ability to stop and later resume interactive segmentation sessions is specially important for tridimensional images and video. However, very often crucial data (e.g., the history of user input) are no longer available; or are no longer reliable, as consequence of some post-processing. How to offer a comprehensive recovery and resume capability, comprising all these different scenarios, under the framework of the "Image Foresting Transform" (IFT) is the central focus of this paper.
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