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.