- scipy.ndimage.measurements.watershed_ift(input, markers, structure=None, output=None)¶
Apply watershed from markers using image foresting transform algorithm.
input : array_like
markers : array_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.
structure : structure 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.
out : ndarray
An output array can optionally be provided. The same shape as input.
watershed_ift : ndarray
Output. Same shape as input.
[R96] 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.