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Some corrections

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François Boulogne
2016-06-01 09:17:36 +02:00
parent ecb84e7362
commit 12fabff65f
3 changed files with 34 additions and 35 deletions
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doc/examples/segmentation/plot_thresholding.py
+7 -7
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@@ -7,11 +7,11 @@ Thresholding is used to create a binary image from a grayscale image [1]_.
Thresholding algorithms can be separated in two categories:
* Histogram-based. The histogram of the pixel intensity is used and
assumptions may be made on the properties of this histogram (e.g. bimodal).
- Histogram-based. The histogram of the pixel intensity is used and
assumptions may be made on the properties of this histogram (e.g. bimodal).
- Local. To process a pixel, only the neighboring pixels are used.
These algorithms often require more computation time.
* Local. To process a pixel, only the neighboring pixels are used.
These algorithms often require more computation time.
Scikit-image includes a function to test thresholding algorithms provided
in the library. Therefore, in a glance, you can select the best algorithm
@@ -30,9 +30,9 @@ img = page()
# Here, we specify a radius for local thresholding algorithm.
# If it is not specified, only global algorithms are called.
fig, ax = thresholding.mosaic_threshold(img, radius=20,
figsize=(10,8), verbose=False)
fig.show()
fig, ax = thresholding.try_all_threshold(img, radius=20,
figsize=(10,8), verbose=False)
plt.show()
"""