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fixed some typos

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Johannes Schönberger
2012-04-25 23:44:06 +02:00
parent 238d4eb4ad
commit d81650f992
2 changed files with 4 additions and 4 deletions
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doc/examples/plot_thresholding.py
+2 -2
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@@ -10,8 +10,8 @@ calculates an "optimal" threshold (marked by a red line in the histogram below)
by maximizing the variance between two classes of pixels, which are separated by
the threshold. Equivalently, this threshold minimizes the intra-class variance.
Additionnally an adaptive thresholding is applied. Also known as local or
dynamic thresholding where the the threshold value is the weighted mean for the
Additionally an adaptive thresholding is applied. Also known as local or
dynamic thresholding where the threshold value is the weighted mean for the
local neighborhood of a pixel subtracted by a constant.
.. [1] http://en.wikipedia.org/wiki/Otsu's_method
skimage/filter/thresholding.py
+2 -2
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@@ -10,8 +10,8 @@ __all__ = ['threshold_otsu', 'adaptive_threshold']
def adaptive_threshold(image, block_size, offset, method='gaussian'):
"""Applies an adaptive threshold to an array.
Also known as local or dynamic thresholding where the the threshold value is
the weighted mean for the local neighborhood of a pixel subtracted by a
Also known as local or dynamic thresholding where the threshold value is the
weighted mean for the local neighborhood of a pixel subtracted by a
constant.
Parameters