mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-27 23:39:49 +08:00
Johannes Schönberger
70 lines
2.0 KiB
Python
70 lines
2.0 KiB
Python
import numpy as np
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from scipy.ndimage import label
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def clear_border(image, buffer_size=0, bgval=0):
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"""Clear objects connected to image border.
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The changes will be applied to the input image.
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Parameters
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----------
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image : (N, M) array
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Binary image.
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buffer_size : int, optional
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Define additional buffer around image border.
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bgval : float or int, optional
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Value for cleared objects.
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Returns
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-------
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image : (N, M) array
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Cleared binary image.
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Examples
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--------
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>>> import numpy as np
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>>> from skimage.segmentation import clear_border
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>>> image = np.array([[0, 0, 0, 0, 0, 0, 0, 1, 0],
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... [0, 0, 0, 0, 1, 0, 0, 0, 0],
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... [1, 0, 0, 1, 0, 1, 0, 0, 0],
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... [0, 0, 1, 1, 1, 1, 1, 0, 0],
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... [0, 1, 1, 1, 1, 1, 1, 1, 0],
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... [0, 0, 0, 0, 0, 0, 0, 0, 0]])
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>>> clear_border(image)
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array([[0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 1, 0, 0, 0, 0],
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[0, 0, 0, 1, 0, 1, 0, 0, 0],
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[0, 0, 1, 1, 1, 1, 1, 0, 0],
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[0, 1, 1, 1, 1, 1, 1, 1, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0]])
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"""
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rows, cols = image.shape
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if buffer_size >= rows or buffer_size >= cols:
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raise ValueError("buffer size may not be greater than image size")
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# create borders with buffer_size
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borders = np.zeros_like(image, dtype=np.bool_)
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ext = buffer_size + 1
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borders[:ext] = True
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borders[- ext:] = True
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borders[:, :ext] = True
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borders[:, - ext:] = True
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labels, number = label(image)
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# determine all objects that are connected to borders
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borders_indices = np.unique(labels[borders])
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indices = np.arange(number + 1)
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# mask all label indices that are connected to borders
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label_mask = np.in1d(indices, borders_indices)
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# create mask for pixels to clear
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mask = label_mask[labels.ravel()].reshape(labels.shape)
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# clear border pixels
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image[mask] = bgval
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return image
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