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  Cooperative Cuts for Image Segmentation

Jegelka, S., & Bilmes, J.(2010). Cooperative Cuts for Image Segmentation (UWEETR-1020-0003). Seattle, WA, USA: Department of Electrical Engineering, University of Washington.

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Jegelka, S1, 2, Autor           
Bilmes, J, Autor           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Zusammenfassung: We propose a novel framework for graph-based cooperative regularization that uses submodular costs on graph edges. We introduce an efficient iterative algorithm to solve the resulting hard discrete optimization problem, and show that it has a guaranteed approximation factor. The edge-submodular formulation is amenable to the same extensions as standard graph cut approaches, and applicable to a range of problems. We apply this method to the image segmentation problem. Specifically, Here, we apply it to introduce a discount for homogeneous boundaries in binary image segmentation on very difficult images, precisely, long thin objects and color and grayscale images with a shading gradient. The experiments show that significant portions of previously truncated objects are now preserved.

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 Datum: 2010-08
 Publikationsstatus: Erschienen
 Seiten: 21
 Ort, Verlag, Ausgabe: Seattle, WA, USA : Department of Electrical Engineering, University of Washington
 Inhaltsverzeichnis: -
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 Identifikatoren: Reportnr.: UWEETR-1020-0003
BibTex Citekey: 6732
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Titel: UWEE Technical Report
Genre der Quelle: Reihe
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Seiten: - Band / Heft: UWEETR-1020-0003 Artikelnummer: - Start- / Endseite: 1 - 21 Identifikator: -