147 lines
4.7 KiB
Python
147 lines
4.7 KiB
Python
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"""
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Binary morphological operations
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"""
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import numpy as np
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from scipy import ndimage as ndi
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from .misc import default_selem
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# The default_selem decorator provides a diamond structuring element as default
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# with the same dimension as the input image and size 3 along each axis.
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@default_selem
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def binary_erosion(image, selem=None, out=None):
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"""Return fast binary morphological erosion of an image.
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This function returns the same result as greyscale erosion but performs
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faster for binary images.
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Morphological erosion sets a pixel at ``(i,j)`` to the minimum over all
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pixels in the neighborhood centered at ``(i,j)``. Erosion shrinks bright
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regions and enlarges dark regions.
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Parameters
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----------
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image : ndarray
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Binary input image.
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selem : ndarray, optional
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The neighborhood expressed as a 2-D array of 1's and 0's.
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If None, use a cross-shaped structuring element (connectivity=1).
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out : ndarray of bool, optional
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The array to store the result of the morphology. If None is
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passed, a new array will be allocated.
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Returns
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-------
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eroded : ndarray of bool or uint
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The result of the morphological erosion taking values in
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``[False, True]``.
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"""
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if out is None:
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out = np.empty(image.shape, dtype=bool)
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ndi.binary_erosion(image, structure=selem, output=out, border_value=True)
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return out
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@default_selem
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def binary_dilation(image, selem=None, out=None):
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"""Return fast binary morphological dilation of an image.
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This function returns the same result as greyscale dilation but performs
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faster for binary images.
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Morphological dilation sets a pixel at ``(i,j)`` to the maximum over all
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pixels in the neighborhood centered at ``(i,j)``. Dilation enlarges bright
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regions and shrinks dark regions.
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Parameters
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----------
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image : ndarray
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Binary input image.
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selem : ndarray, optional
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The neighborhood expressed as a 2-D array of 1's and 0's.
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If None, use a cross-shaped structuring element (connectivity=1).
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out : ndarray of bool, optional
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The array to store the result of the morphology. If None is
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passed, a new array will be allocated.
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Returns
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-------
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dilated : ndarray of bool or uint
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The result of the morphological dilation with values in
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``[False, True]``.
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"""
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if out is None:
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out = np.empty(image.shape, dtype=bool)
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ndi.binary_dilation(image, structure=selem, output=out)
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return out
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@default_selem
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def binary_opening(image, selem=None, out=None):
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"""Return fast binary morphological opening of an image.
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This function returns the same result as greyscale opening but performs
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faster for binary images.
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The morphological opening on an image is defined as an erosion followed by
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a dilation. Opening can remove small bright spots (i.e. "salt") and connect
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small dark cracks. This tends to "open" up (dark) gaps between (bright)
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features.
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Parameters
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----------
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image : ndarray
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Binary input image.
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selem : ndarray, optional
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The neighborhood expressed as a 2-D array of 1's and 0's.
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If None, use a cross-shaped structuring element (connectivity=1).
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out : ndarray of bool, optional
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The array to store the result of the morphology. If None
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is passed, a new array will be allocated.
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Returns
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-------
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opening : ndarray of bool
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The result of the morphological opening.
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"""
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eroded = binary_erosion(image, selem)
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out = binary_dilation(eroded, selem, out=out)
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return out
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@default_selem
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def binary_closing(image, selem=None, out=None):
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"""Return fast binary morphological closing of an image.
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This function returns the same result as greyscale closing but performs
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faster for binary images.
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The morphological closing on an image is defined as a dilation followed by
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an erosion. Closing can remove small dark spots (i.e. "pepper") and connect
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small bright cracks. This tends to "close" up (dark) gaps between (bright)
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features.
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Parameters
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----------
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image : ndarray
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Binary input image.
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selem : ndarray, optional
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The neighborhood expressed as a 2-D array of 1's and 0's.
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If None, use a cross-shaped structuring element (connectivity=1).
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out : ndarray of bool, optional
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The array to store the result of the morphology. If None,
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is passed, a new array will be allocated.
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Returns
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-------
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closing : ndarray of bool
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The result of the morphological closing.
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"""
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dilated = binary_dilation(image, selem)
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out = binary_erosion(dilated, selem, out=out)
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return out
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