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dc.contributor.authorSchmitt, Michel
dc.contributor.authorNajman, Laurent
dc.date.accessioned2012-10-24T14:13:42Z
dc.date.available2012-10-24T14:13:42Z
dc.date.issued1996
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/10495
dc.language.isoenen
dc.subjectwatersheden
dc.subjectmorphological segmentationen
dc.subjectdynamics
dc.subjecthierarchical segmentation
dc.subjectgeodesic reconstruction
dc.subject.ddc006.3en
dc.titleGeodesic Saliency of Watershed Contours and Hierarchical Segmentationen
dc.typeArticle accepté pour publication ou publié
dc.contributor.editoruniversityotherCentre de Géostatistique Mines ParisTech;France
dc.description.abstractenThe watershed is one of the latest segmentation tools developed in mathematical morphology. In order to prevent its oversegmentation, the notion of dynamics of a minimum, based on geodesic reconstruction, has been proposed. In this paper, we extend the notion of dynamics to the contour arcs. This notion acts as a measure of the saliency of the contour. Contrary to the dynamics of minima, our concept reflects the extension and shape of the corresponding object in the image. This representation is also much more natural, because it is expressed in terms of partitions of the plane, i.e., segmentations. A hierarchical segmentation process is then derived, which gives a compact description of the image, containing all the segmentations one can obtain by the notion of dynamics, by means of a simple thresholding. Finally, efficient algorithms for computing the geodesic reconstruction as well as the dynamics of contours are presented.en
dc.relation.isversionofjnlnameIEEE Transactions on Pattern Analysis and Machine Intelligence
dc.relation.isversionofjnlvol18en
dc.relation.isversionofjnlissue12en
dc.relation.isversionofjnldate1996
dc.relation.isversionofjnlpages1163-1173en
dc.relation.isversionofdoihttp://dx.doi.org/10.1109/34.546254en
dc.identifier.urlsitehttp://hal-upec-upem.archives-ouvertes.fr/hal-00622128en
dc.relation.isversionofjnlpublisherIEEEen
dc.subject.ddclabelIntelligence artificielleen
dc.relation.forthcomingnonen
dc.relation.forthcomingprintnonen


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