`scipy.ndimage._morphology:binary_dilation`

source: /scipy/ndimage/_morphology.py :407

Signature

   def     binary_dilation (    input    ,    structure    =  None   ,    iterations    =  1   ,    mask    =  None   ,    output    =  None   ,    border_value    =  0   ,    origin    =  0   ,    brute_force    =  False   ,  * ,     axes    =  None     )

Summary

Multidimensional binary dilation with the given structuring element.

Parameters

input : array_like: Binary array_like to be dilated. Non-zero (True) elements form the subset to be dilated.
structure : array_like, optional: Structuring element used for the dilation. 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 dilation is repeated iterations times (one, by default). If iterations is less than 1, the dilation is repeated until the result does not change anymore. Only an integer of iterations is accepted.
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 (dilated) in the current iteration; if True all pixels are considered as candidates for dilation, regardless of what happened in the previous iteration. False by default.
axes : tuple of int or None: The axes over which to apply the filter. If None, input is filtered along all axes. If an origin tuple is provided, its length must match the number of axes.

Returns

binary_dilation : ndarray of bools: Dilation of the input by the structuring element.

Notes

Dilation ^[1] is a mathematical morphology operation ^[2] that uses a structuring element for expanding the shapes in an image. The binary dilation of an image by a structuring element is the locus of the points covered by the structuring element, when its center lies within the non-zero points of the image.

Array API Standard Support

binary_dilation has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

====================  ====================  ====================
Library               CPU                   GPU
====================  ====================  ====================
NumPy                 ✅                     n/a                 
CuPy                  n/a                   ✅                   
PyTorch               ✅                     ⛔                   
JAX                   ⚠️ no JIT             ⛔                   
Dask                  ⚠️ computes graph     n/a                 
====================  ====================  ====================

See dev-arrayapi for more information.

Examples

from scipy import ndimage
import numpy as np
a = np.zeros((5, 5))
a[2, 2] = 1

✓

a
ndimage.binary_dilation(a)
ndimage.binary_dilation(a).astype(a.dtype)

✗

struct1 = ndimage.generate_binary_structure(2, 1)

✓

struct1

✗

struct2 = ndimage.generate_binary_structure(2, 2)

✓

struct2
ndimage.binary_dilation(a, structure=struct1).astype(a.dtype)
ndimage.binary_dilation(a, structure=struct2).astype(a.dtype)
ndimage.binary_dilation(a, structure=struct1,\
iterations=2).astype(a.dtype)

✗

Aliases

scipy.ndimage.binary_dilation