erosion(image, selem=None, out=None, shift_x=False, shift_y=False)
Morphological erosion sets a pixel at (i,j) to the minimum over all pixels in the neighborhood centered at (i,j). Erosion shrinks bright regions and enlarges dark regions.
For uint8
(and uint16
up to a certain bit-depth) data, the lower algorithm complexity makes the skimage.filters.rank.minimum
function more efficient for larger images and structuring elements.
Image array.
The neighborhood expressed as an array of 1's and 0's. If None, use cross-shaped structuring element (connectivity=1).
The array to store the result of the morphology. If None is passed, a new array will be allocated.
shift structuring element about center point. This only affects eccentric structuring elements (i.e. selem with even numbered sides).
The result of the morphological erosion.
Return greyscale morphological erosion of an image.
>>> # Erosion shrinks bright regionsSee :
... import numpy as np
... from skimage.morphology import square
... bright_square = np.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=np.uint8)
... erosion(bright_square, square(3)) 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=uint8)
The following pages refer to to this document either explicitly or contain code examples using this.
skimage.morphology.grey.erosion
skimage.filters.rank.generic.minimum
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