Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Image Analysis |
| Untertitel | 17th Scandinavian Conference, SCIA 2011, Proceedings |
| Seiten | 656-665 |
| Seitenumfang | 10 |
| Publikationsstatus | Veröffentlicht - 2011 |
| Veranstaltung | 17th Scandinavian Conference on Image Analysis, SCIA 2011 - Ystad, Schweden Dauer: 23 Mai 2011 → 27 Mai 2011 |
Publikationsreihe
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Band | 6688 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (elektronisch) | 1611-3349 |
Abstract
Variational frameworks based on level set methods are popular for the general problem of image segmentation. They combine different feature channels in an energy minimization approach. In contrast to other popular segmentation frameworks, e.g. the graph cut framework, current level set formulations do not allow much user interaction. Except for selecting the initial boundary, the user is barely able to guide or correct the boundary propagation. Based on Dempster-Shafer theory of evidence we propose a segmentation framework which integrates user interaction in a novel way. Given the input image, the proposed algorithm determines the best segmentation allowing the user to take global influence on the boundary propagation.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Theoretische Informatik
- Informatik (insg.)
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Image Analysis: 17th Scandinavian Conference, SCIA 2011, Proceedings. 2011. S. 656-665 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 6688 LNCS).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Interactive image segmentation using level sets and Dempster-Shafer theory of evidence
AU - Scheuermann, Björn
AU - Rosenhahn, Bodo
N1 - Funding information: This work is partially funded by the German Research Foundation (RO 2497/6-1).
PY - 2011
Y1 - 2011
N2 - Variational frameworks based on level set methods are popular for the general problem of image segmentation. They combine different feature channels in an energy minimization approach. In contrast to other popular segmentation frameworks, e.g. the graph cut framework, current level set formulations do not allow much user interaction. Except for selecting the initial boundary, the user is barely able to guide or correct the boundary propagation. Based on Dempster-Shafer theory of evidence we propose a segmentation framework which integrates user interaction in a novel way. Given the input image, the proposed algorithm determines the best segmentation allowing the user to take global influence on the boundary propagation.
AB - Variational frameworks based on level set methods are popular for the general problem of image segmentation. They combine different feature channels in an energy minimization approach. In contrast to other popular segmentation frameworks, e.g. the graph cut framework, current level set formulations do not allow much user interaction. Except for selecting the initial boundary, the user is barely able to guide or correct the boundary propagation. Based on Dempster-Shafer theory of evidence we propose a segmentation framework which integrates user interaction in a novel way. Given the input image, the proposed algorithm determines the best segmentation allowing the user to take global influence on the boundary propagation.
UR - http://www.scopus.com/inward/record.url?scp=79957446990&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-21227-7_61
DO - 10.1007/978-3-642-21227-7_61
M3 - Conference contribution
AN - SCOPUS:79957446990
SN - 9783642212260
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 656
EP - 665
BT - Image Analysis
T2 - 17th Scandinavian Conference on Image Analysis, SCIA 2011
Y2 - 23 May 2011 through 27 May 2011
ER -