dilation
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skimage.morphology.dilation(image, selem=None, *args, **kwargs)
[source] -
Return greyscale morphological dilation of an image.
Morphological dilation sets a pixel at (i,j) to the maximum over all pixels in the neighborhood centered at (i,j). Dilation enlarges bright regions and shrinks dark regions.
Parameters: image : ndarray
Image array.
selem : ndarray, optional
The neighborhood expressed as a 2-D array of 1’s and 0’s. If None, use cross-shaped structuring element (connectivity=1).
out : ndarray, optional
The array to store the result of the morphology. If None, is passed, a new array will be allocated.
shift_x, shift_y : bool, optional
shift structuring element about center point. This only affects eccentric structuring elements (i.e. selem with even numbered sides).
Returns: dilated : uint8 array, same shape and type as
image
The result of the morphological dilation.
Notes
For
uint8
(anduint16
up to a certain bit-depth) data, the lower algorithm complexity makes theskimage.filter.rank.maximum
function more efficient for larger images and structuring elements.Examples
>>> # Dilation enlarges bright regions >>> import numpy as np >>> from skimage.morphology import square >>> bright_pixel = np.array([[0, 0, 0, 0, 0], ... [0, 0, 0, 0, 0], ... [0, 0, 1, 0, 0], ... [0, 0, 0, 0, 0], ... [0, 0, 0, 0, 0]], dtype=np.uint8) >>> dilation(bright_pixel, square(3)) 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]], dtype=uint8)
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