erosion

erosion

skimage.morphology.erosion(image, selem=None, *args, **kwargs) [source]

Return greyscale morphological erosion of an image.

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.

Parameters:

image : ndarray Image array. selem : ndarray, optional The neighborhood expressed as an array of 1’s and 0’s. If None, use cross-shaped structuring element (connectivity=1). out : ndarrays, 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:

eroded : array, same shape as image The result of the morphological erosion.

Notes

For uint8 (and uint16 up to a certain bit-depth) data, the lower algorithm complexity makes the skimage.filter.rank.minimum function more efficient for larger images and structuring elements.

Examples

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>>> # Erosion shrinks bright regions >>> 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)