prtools.binary_closing#

binary_closing(input, structure=None, iterations=1, mask=None, output=None, border_value=0)[source]#

Binary closing using the given structure element.

The closing of an input image is the erosion of the dilation of the image by the structure element.

Parameters:

  • input (array_like) – Array to be closed. Nonzero elements form the subset to be closed.

  • structure (array_like, optional) – Structure element used for closing. Nonzero elements are considered True. If None (default), a structure element with a square connectivity equal to one is used.

  • iterations (int, optional) – Number of times to repeat the closing. Default is 1.

  • mask (array_like, optional) – Mask applied to the inputs where a True value indicates the corresponding input element should be included in the closing.

  • output (ndarray, optional) –

    Array location into which the result is stored. If None (default), a freshly-allocated array is returned.

    Note

    output must be None if input is a JAX array.

  • border_value (int (cast to 0 or 1), optional) – Value at the border of the output array.

Returns:

binary_closing – Closing of the input by the structure element.

Return type:

ndarray of bools

See also

binary_dilation(), binary_erosion(), binary_opening()

Notes

This function is designed to be compatible with JAX jit and grad operations.

Examples

>>> a = np.zeros((5,5), dtype=int)
>>> a[1:-1, 1:-1] = 1; a[2,2] = 0
>>> a
array([[0, 0, 0, 0, 0],
       [0, 1, 1, 1, 0],
       [0, 1, 0, 1, 0],
       [0, 1, 1, 1, 0],
       [0, 0, 0, 0, 0]])

>>> # Closing removes small holes
>>> prtools.binary_closing(a).astype(int)
array([[0, 0, 0, 0, 0],
       [0, 1, 1, 1, 0],
       [0, 1, 1, 1, 0],
       [0, 1, 1, 1, 0],
       [0, 0, 0, 0, 0]])

>>> a = np.zeros((7,7), dtype=int)
>>> a[1:6, 2:5] = 1; a[1:3,3] = 0
>>> a
array([[0, 0, 0, 0, 0, 0, 0],
       [0, 0, 1, 0, 1, 0, 0],
       [0, 0, 1, 0, 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]])

>>> # Closing can also coarsen boundaries with fine hollows
>>> prtools.binary_closing(a).astype(int)
array([[0, 0, 0, 0, 0, 0, 0],
       [0, 0, 1, 0, 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]])