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)[source]¶ Multidimensional binary erosion with a given structuring element.
Binary erosion is a mathematical morphology operation used for image processing.
 Parameters
 inputarray_like
Binary image to be eroded. Nonzero (True) elements form the subset to be eroded.
 structurearray_like, optional
Structuring element used for the erosion. Nonzero elements are considered True. If no structuring element is provided, an element is generated with a square connectivity equal to one.
 iterationsint, 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.
 maskarray_like, optional
If a mask is given, only those elements with a True value at the corresponding mask element are modified at each iteration.
 outputndarray, optional
Array of the same shape as input, into which the output is placed. By default, a new array is created.
 border_valueint (cast to 0 or 1), optional
Value at the border in the output array.
 originint or tuple of ints, optional
Placement of the filter, by default 0.
 brute_forceboolean, 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_erosionndarray of bools
Erosion of the input by the structuring element.
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 nonzero elements of the image.
References
Examples
>>> from scipy import ndimage >>> 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]])