Labelisation watershed
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Watershed cut of the given edge weighted graph. |
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Seeded watershed cut on an edge weighted graph. |
- labelisation_watershed(graph, edge_weights)[source]
Watershed cut of the given edge weighted graph.
The definition and algorithm used are described in:
J. Cousty, G. Bertrand, L. Najman and M. Couprie. Watershed cuts: minimum spanning forests, and the drop of water principle. IEEE Trans. on Pattern Analysis and Machine Intelligence, 31(8): 1362-1374, 2009.
The watershed cut is represented by a labelisation of the graph vertices.
- Complexity:
This algorithm has a linear runtime complexity \(\mathcal{O}(n)\) with \(n\) the number of edges in the graph.
- Parameters:
graph – input graph
edge_weights – Weights on the edges of the graph
- Returns:
A labelisation of the graph vertices
- labelisation_seeded_watershed(graph, edge_weights, vertex_seeds, background_label=0)[source]
Seeded watershed cut on an edge weighted graph. Seeds and associated labels are given in
vertex_seeds
. A vertex \(v\), such that \(vertex\_seeds(v)\neq background\_label\) is a seed with associated label \(vertex\_seeds(v)\).The label of a vertex of the graph is then defined equal to the label of the closest seed in the edge weighted graph for the min-max distance. If several such seeds exist (eg. on a plateus between two seeds), an arbitrary and consistent choice is made ensuring that:
each flat zone of level \(k\) of the final labelling contains at least one seed with the label \(k\); and
each seed is contained in a flat zone whose level is equal to the seed label.
- Complexity:
This algorithm has a runtime complexity in \(\mathcal{O}(n \log n)\) with \(n\) the number of edges in the graph.
- Parameters:
graph – Input graph
edge_weights – Weights on the edges of the graph
vertex_seeds – Seeds with integer label values on the vertices of the graph
background_label – Vertices whose values are equal to
background_label
(default 0) invertex_seeds
are not considered as seeds
- Returns:
A labelisation of the graph vertices