skimage 0.17.2

ParametersReturnsBackRef
join_segmentations(s1, s2)

The join J of S1 and S2 is defined as the segmentation in which two voxels are in the same segment if and only if they are in the same segment in both S1 and S2.

Parameters

s1, s2 : numpy arrays

s1 and s2 are label fields of the same shape.

Returns

j : numpy array

The join segmentation of s1 and s2.

Return the join of the two input segmentations.

Examples

This example is valid syntax, but we were not able to check execution
>>> from skimage.segmentation import join_segmentations
... s1 = np.array([[0, 0, 1, 1],
...  [0, 2, 1, 1],
...  [2, 2, 2, 1]])
... s2 = np.array([[0, 1, 1, 0],
...  [0, 1, 1, 0],
...  [0, 1, 1, 1]])
... join_segmentations(s1, s2) array([[0, 1, 3, 2], [0, 5, 3, 2], [4, 5, 5, 3]])
See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

skimage.segmentation._join.join_segmentations

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


File: /skimage/segmentation/_join.py#6
type: <class 'function'>
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