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https://github.com/wassname/scikit-image.git
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Olivier Debeir
50 lines
1.3 KiB
Python
50 lines
1.3 KiB
Python
"""
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=====================
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Local Otsu Threshold
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=====================
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This example shows how Otsu's threshold [1]_ method can be applied locally.
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For each pixel, an "optimal" threshold is determined by maximizing the variance between two classes of pixels
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of the local neighborhood defined by a structuring element.
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The example compares the local threshold with the global threshold.
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.. note: local threshold is much slower than global one.
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.. [1] http://en.wikipedia.org/wiki/Otsu's_method
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"""
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import matplotlib.pyplot as plt
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from skimage import data
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from skimage.morphology.selem import disk
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import skimage.filter.rank as rank
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from skimage.filter import threshold_otsu
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p8 = data.page()
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radius = 10
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selem = disk(radius)
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loc_otsu = rank.otsu(p8, selem)
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t_glob_otsu = threshold_otsu(p8)
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glob_otsu = p8 >= t_glob_otsu
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plt.figure()
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plt.subplot(2, 2, 1)
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plt.imshow(p8, cmap=plt.cm.gray)
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plt.xlabel('original')
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plt.colorbar()
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plt.subplot(2, 2, 2)
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plt.imshow(loc_otsu, cmap=plt.cm.gray)
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plt.xlabel('local Otsu ($radius=%d$)' % radius)
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plt.colorbar()
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plt.subplot(2, 2, 3)
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plt.imshow(p8 >= loc_otsu, cmap=plt.cm.gray)
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plt.xlabel('original>=local Otsu' % t_glob_otsu)
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plt.subplot(2, 2, 4)
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plt.imshow(glob_otsu, cmap=plt.cm.gray)
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plt.xlabel('global Otsu ($t=%d$)' % t_glob_otsu)
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plt.show()
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