machinevisiontoolbox.Image.erode
- Image.erode(se, n=1, border='replicate', bordervalue=0, **kwargs)
Morphological erosion
- Parameters:
se (ndarray(N,M)) – structuring element
n (int, optional) – number of times to apply the erosion, defaults to 1
border (str, optional) – option for boundary handling, see
convolve, defaults to ‘replicate’bordervalue (scalar, optional) – padding value, defaults to 0
kwargs – addition options passed to
opencv.erode
- Returns:
eroded image
- Return type:
Image
Returns the image after morphological erosion with the structuring element
seappliedntimes.Example:
>>> from machinevisiontoolbox import Image >>> import numpy as np >>> img = Image.Squares(1,7) >>> img.print() 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 1 1 1 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 >>> img.erode(np.ones((3,3))).print() 0 0 0 0 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
- Note:
It is cheaper to apply a smaller structuring element multiple times than one large one, the effective structuing element is the Minkowski sum of the structuring element with itself N times.
The structuring element typically has odd side lengths.
For a greyscale image this is the maximum value over the structuring element.
- References:
Robotics, Vision & Control for Python, Section 11.6, P. Corke, Springer 2023.
- Seealso: