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scipy.ndimage.

# watershed_ift

scipy.ndimage.watershed_ift(input, markers, structure=None, output=None)

  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.