Graph segmentation techniques are often used in image processing since an image can be seen as a weighted graph. In this thesis, we show some links existing between several weighted graph segmentation paradigms. We first present different definitions of watersheds and select the one which framework allows comparison with specific spanning forests. We show that such a watershed relative to arbitrary markers is equivalent to a cut induced by a shortest path spanning forest. Then, cuts induced by minimum spanning forests are demonstrated as being particular cases which advantageously avoid some undesirable results. Finally, we show that minimum cuts coincide with cuts induced by maximum spanning forests for some particular weight functions. In...
International audienceMathematical morphology has developed a powerful methodology for segmenting im...
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Ci...
Image segmentation is a fundamental problem in computer vision. Despite many years of research, gene...
Graph segmentation techniques are often used in image processing since an image can be seen as a wei...
Les techniques de segmentation de graphe sont souvent utilisées en traitement d’images puisque ces d...
International audienceIn this work, we extend a common framework for graph-based image segmentation ...
International audienceMinimum cuts, extremum spanning forests and watersheds have been used as the b...
International audienceWe recently introduced the watershed cuts, a notion of watershed in edge-weigh...
International audienceIn this paper, we discuss the use of graph-cuts to merge the re gions of the w...
International audienceWe study the watersheds in edge-weighted graphs. We define the watershed cuts ...
In this paper, we study the watersheds in edge-weighted graphs. Contrarily to previous work, we defi...
In this paper, we discuss the use of graph-cuts to merge the regions of the watershed transform opti...
Medical imaging is one of the most active research topics in image analysis. Analyzing and segmentin...
In this lecture, we will consider two special types of graphs: forests and trees. A forest is a grap...
The notion of a cleft models a frontier in a graph. Merging two regions, as requested by some image ...
International audienceMathematical morphology has developed a powerful methodology for segmenting im...
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Ci...
Image segmentation is a fundamental problem in computer vision. Despite many years of research, gene...
Graph segmentation techniques are often used in image processing since an image can be seen as a wei...
Les techniques de segmentation de graphe sont souvent utilisées en traitement d’images puisque ces d...
International audienceIn this work, we extend a common framework for graph-based image segmentation ...
International audienceMinimum cuts, extremum spanning forests and watersheds have been used as the b...
International audienceWe recently introduced the watershed cuts, a notion of watershed in edge-weigh...
International audienceIn this paper, we discuss the use of graph-cuts to merge the re gions of the w...
International audienceWe study the watersheds in edge-weighted graphs. We define the watershed cuts ...
In this paper, we study the watersheds in edge-weighted graphs. Contrarily to previous work, we defi...
In this paper, we discuss the use of graph-cuts to merge the regions of the watershed transform opti...
Medical imaging is one of the most active research topics in image analysis. Analyzing and segmentin...
In this lecture, we will consider two special types of graphs: forests and trees. A forest is a grap...
The notion of a cleft models a frontier in a graph. Merging two regions, as requested by some image ...
International audienceMathematical morphology has developed a powerful methodology for segmenting im...
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Ci...
Image segmentation is a fundamental problem in computer vision. Despite many years of research, gene...