
Boundary Extraction in Natural Images Using Ultrametric Contour Maps
Arbelaez, Pablo (2006), Boundary Extraction in Natural Images Using Ultrametric Contour Maps, Conference on Computer Vision and Pattern Recognition Workshop, 2006. CVPRW '06. Proceedings, IEEE, p. 182. http://dx.doi.org/10.1109/CVPRW.2006.48
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Type
Communication / ConférenceDate
2006Conference title
Conference on Computer Vision and Pattern Recognition Workshop, 2006. CVPRW '06Conference date
2006-06Conference city
New YorkConference country
États-UnisBook title
Conference on Computer Vision and Pattern Recognition Workshop, 2006. CVPRW '06. ProceedingsPublisher
IEEE
ISBN
0-7695-2646-2
Pages
182
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Arbelaez, PabloAbstract (EN)
This paper presents a low-level system for boundary extraction and segmentation of natural images and the evaluation of its performance. We study the problem in the framework of hierarchical classification, where the geometric structure of an image can be represented by an ultrametric contour map, the soft boundary image associated to a family of nested segmentations. We define generic ultrametric distances by integrating local contour cues along the regions boundaries and combining this information with region attributes. Then, we evaluate quantitatively our results with respect to ground-truth segmentation data, proving that our system outperforms significantly two widely used hierarchical segmentation techniques, as well as the state of the art in local edge detection.Subjects / Keywords
segmentation techniques; Computer visionRelated items
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