mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-28 02:30:57 +08:00
Johannes Schönberger
52 lines
1.3 KiB
Python
52 lines
1.3 KiB
Python
"""
|
|
====================
|
|
Local Otsu Threshold
|
|
====================
|
|
|
|
This example shows how Otsu's threshold [1]_ method can be applied locally. For
|
|
each pixel, an "optimal" threshold is determined by maximizing the variance
|
|
between two classes of pixels of the local neighborhood defined by a structuring
|
|
element.
|
|
|
|
The example compares the local threshold with the global threshold.
|
|
|
|
.. note: local is much slower than global thresholding
|
|
|
|
.. [1] http://en.wikipedia.org/wiki/Otsu's_method
|
|
|
|
"""
|
|
import matplotlib.pyplot as plt
|
|
|
|
from skimage import data
|
|
from skimage.morphology import disk
|
|
from skimage.filter import threshold_otsu, rank
|
|
from skimage.util import img_as_ubyte
|
|
|
|
|
|
p8 = img_as_ubyte(data.page())
|
|
|
|
radius = 10
|
|
selem = disk(radius)
|
|
|
|
loc_otsu = rank.otsu(p8, selem)
|
|
t_glob_otsu = threshold_otsu(p8)
|
|
glob_otsu = p8 >= t_glob_otsu
|
|
|
|
|
|
plt.figure()
|
|
plt.subplot(2, 2, 1)
|
|
plt.imshow(p8, cmap=plt.cm.gray)
|
|
plt.xlabel('original')
|
|
plt.colorbar()
|
|
plt.subplot(2, 2, 2)
|
|
plt.imshow(loc_otsu, cmap=plt.cm.gray)
|
|
plt.xlabel('local Otsu ($radius=%d$)' % radius)
|
|
plt.colorbar()
|
|
plt.subplot(2, 2, 3)
|
|
plt.imshow(p8 >= loc_otsu, cmap=plt.cm.gray)
|
|
plt.xlabel('original >= local Otsu' % t_glob_otsu)
|
|
plt.subplot(2, 2, 4)
|
|
plt.imshow(glob_otsu, cmap=plt.cm.gray)
|
|
plt.xlabel('global Otsu ($t = %d$)' % t_glob_otsu)
|
|
plt.show()
|