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bundles / skimage latest / skimage / morphology / gray / opening

function

skimage.morphology.gray:opening

source: /dev/scikit-image/src/skimage/morphology/gray.py :333

Signature

def   opening ( image ,  footprint = None ,  out = None ,  * ,  mode = reflect ,  cval = 0.0 )

Summary

Return grayscale morphological opening of an image.

Extended Summary

The morphological opening of an image is defined as an erosion followed by a dilation. Opening can remove small bright spots (i.e. "salt") and connect small dark cracks. This tends to "open" up (dark) gaps between (bright) features.

Parameters

image : ndarray

Image array.

footprint : ndarray or tuple, optional

The neighborhood expressed as a 2-D array of 1's and 0's. If None, use a cross-shaped footprint (connectivity=1). The footprint can also be provided as a sequence of smaller footprints as described in the notes below.

out : ndarray, optional

The array to store the result of the morphology. If None is passed, a new array will be allocated.

mode : str, optional

The mode parameter determines how the array borders are handled. Valid modes are: 'reflect', 'constant', 'nearest', 'mirror', 'wrap', 'max', 'min', or 'ignore'. If 'ignore', pixels outside the image domain are assumed to be the maximum for the image's dtype in the erosion, and minimum in the dilation, which causes them to not influence the result. Default is 'reflect'.

cval : scalar, optional

Value to fill past edges of input if mode is 'constant'. Default is 0.0.

Returns

opening : array, same shape and type as `image`

The result of the morphological opening.

Notes

The footprint can also be a provided as a sequence of 2-tuples where the first element of each 2-tuple is a footprint ndarray and the second element is an integer describing the number of times it should be iterated. For example footprint=[(np.ones((9, 1)), 1), (np.ones((1, 9)), 1)] would apply a 9x1 footprint followed by a 1x9 footprint resulting in a net effect that is the same as footprint=np.ones((9, 9)), but with lower computational cost. Most of the builtin footprints such as skimage.morphology.disk provide an option to automatically generate a footprint sequence of this type.

Examples

import numpy as np
from skimage.morphology import footprint_rectangle
bad_connection = np.array([[1, 0, 0, 0, 1],
                           [1, 1, 0, 1, 1],
                           [1, 1, 1, 1, 1],
                           [1, 1, 0, 1, 1],
                           [1, 0, 0, 0, 1]], dtype=np.uint8)
opening(bad_connection, footprint_rectangle((3, 3)))
✓

Aliases

  • skimage.morphology.opening

Referenced by

This package