# scipy.ndimage.binary_erosion

scipy.ndimage.binary_erosion(input, structure=None, iterations=1, mask=None, output=None, border_value=0, origin=0, brute_force=False)

  Multidimensional binary erosion with a given structuring element.

  Binary erosion is a mathematical morphology operation used for image processing.

  Parameters:
    input array_like

      Binary image to be eroded. Non-zero (True) elements form the subset to be eroded.

    structure array_like, optional

      Structuring element used for the erosion. Non-zero elements are considered True. If no structuring element is provided, an element is generated with a square connectivity equal to one.

    iterations int, optional

      The erosion is repeated iterations times (one, by default). If iterations is less than 1, the erosion is repeated until the result does not change anymore.

    mask array_like, optional

      If a mask is given, only those elements with a True value at the corresponding mask element are modified at each iteration.

    output ndarray, optional

      Array of the same shape as input, into which the output is placed. By default, a new array is created.

    border_value int (cast to 0 or 1), optional

      Value at the border in the output array.

    origin int or tuple of ints, optional

      Placement of the filter, by default 0.

    brute_force boolean, optional

      Memory condition: if False, only the pixels whose value was changed in the last iteration are tracked as candidates to be updated (eroded) in the current iteration; if True all pixels are considered as candidates for erosion, regardless of what happened in the previous iteration. False by default.

  Returns:
    binary_erosion ndarray of bools

      Erosion of the input by the structuring element.

  See also

  `grey_erosion`, `binary_dilation`, `binary_closing`, `binary_opening`
  `generate_binary_structure`

  Notes

  Erosion [1] is a mathematical morphology operation [2] that uses a structuring element for shrinking the shapes in an image. The binary erosion of an image by a structuring element is the locus of the points where a superimposition of the structuring element centered on the point is entirely contained in the set of non-zero elements of the image.

  References

  [1]

  https://en.wikipedia.org/wiki/Erosion_%28morphology%29

  [2]

  https://en.wikipedia.org/wiki/Mathematical_morphology

  Examples

      >>> from scipy import ndimage
      >>> import numpy as np
      >>> a = np.zeros((7,7), dtype=int)
      >>> a[1:6, 2:5] = 1
      >>> a
      array([[0, 0, 0, 0, 0, 0, 0],
             [0, 0, 1, 1, 1, 0, 0],
             [0, 0, 1, 1, 1, 0, 0],
             [0, 0, 1, 1, 1, 0, 0],
             [0, 0, 1, 1, 1, 0, 0],
             [0, 0, 1, 1, 1, 0, 0],
             [0, 0, 0, 0, 0, 0, 0]])
      >>> ndimage.binary_erosion(a).astype(a.dtype)
      array([[0, 0, 0, 0, 0, 0, 0],
             [0, 0, 0, 0, 0, 0, 0],
             [0, 0, 0, 1, 0, 0, 0],
             [0, 0, 0, 1, 0, 0, 0],
             [0, 0, 0, 1, 0, 0, 0],
             [0, 0, 0, 0, 0, 0, 0],
             [0, 0, 0, 0, 0, 0, 0]])
      >>> #Erosion removes objects smaller than the structure
      >>> ndimage.binary_erosion(a, structure=np.ones((5,5))).astype(a.dtype)
      array([[0, 0, 0, 0, 0, 0, 0],
             [0, 0, 0, 0, 0, 0, 0],
             [0, 0, 0, 0, 0, 0, 0],
             [0, 0, 0, 0, 0, 0, 0],
             [0, 0, 0, 0, 0, 0, 0],
             [0, 0, 0, 0, 0, 0, 0],
             [0, 0, 0, 0, 0, 0, 0]])