April 2020
Intermediate to advanced
438 pages
12h 2m
English
Content preview from Python Image Processing Cookbook
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How it works...
In step 1, the threshold_otsu() function from the scikit-image.filters module was used to find the optimal threshold for creating the binary image (by thresholding the grayscale image).
In step 2, the binary_erosion() and binary_dilation() functions from scipy.ndimage were used to apply erosion and dilation operations to a binary image, respectively. These functions accept the binary image to be eroded/dilated, the structuring element to be used (the default SE is a square with connectivity 1), and the number of times the operation is to be repeated (default 1). Non-zero elements are considered True.
As you can observe, np.ones((2,2) was used to create a square SE of size 2, whereas morph.disk(radius=2) was used to generate ...
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