scipy.ndimage.watershed_ift#
- scipy.ndimage.watershed_ift(input, markers, structure=None, output=None)[source]#
Apply watershed from markers using image foresting transform algorithm.
- Parameters
- inputarray_like
Input.
- markersarray_like
Markers are points within each watershed that form the beginning of the process. Negative markers are considered background markers which are processed after the other markers.
- structurestructure element, optional
A structuring element defining the connectivity of the object can be provided. If None, an element is generated with a squared connectivity equal to one.
- outputndarray, optional
An output array can optionally be provided. The same shape as input.
- Returns
- watershed_iftndarray
Output. Same shape as input.
References
- 1
A.X. Falcao, J. Stolfi and R. de Alencar Lotufo, “The image foresting transform: theory, algorithms, and applications”, Pattern Analysis and Machine Intelligence, vol. 26, pp. 19-29, 2004.