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.