mirror of
https://github.com/wassname/scikit-image.git
synced 2026-06-27 20:53:27 +08:00
François Boulogne
62 lines
1.8 KiB
Python
62 lines
1.8 KiB
Python
"""
|
|
============
|
|
Thresholding
|
|
============
|
|
|
|
Thresholding is used to create a binary image from a grayscale image [1]_.
|
|
If you are not familiar with the details of the different algorithms and the
|
|
underlying assumptions, it is often difficult to know which algorithm will give
|
|
the best results. Therefore, Scikit-image includes a function to evaluate
|
|
thresholding algorithms provided by the library. At a glance, you can select
|
|
the best algorithm for you data without a deep understanding of their
|
|
mechanisms.
|
|
|
|
.. [1] https://en.wikipedia.org/wiki/Thresholding_%28image_processing%29
|
|
|
|
.. seealso::
|
|
:ref:`sphx_glr_auto_examples_xx_applications_plot_thresholding.py`
|
|
|
|
"""
|
|
import matplotlib
|
|
import matplotlib.pyplot as plt
|
|
|
|
from skimage import data
|
|
from skimage.filters import thresholding
|
|
|
|
img = data.page()
|
|
|
|
# Here, we specify a radius for local thresholding algorithms.
|
|
# If it is not specified, only global algorithms are called.
|
|
fig, ax = thresholding.try_all_threshold(img, radius=20,
|
|
figsize=(10, 8), verbose=False)
|
|
plt.show()
|
|
|
|
######################################################################
|
|
# How to apply a threshold?
|
|
# =========================
|
|
#
|
|
# Now, we illustrate how to apply one of these thresholding algorithms.
|
|
# This example uses the mean value of pixel intensities. It is a simple
|
|
# and naive threshold value, which is sometimes used as a guess value.
|
|
|
|
from skimage.filters.thresholding import threshold_mean
|
|
from skimage import data
|
|
|
|
image = data.camera()
|
|
thresh = threshold_mean(image)
|
|
binary = image > thresh
|
|
|
|
fig, axes = plt.subplots(ncols=2, figsize=(8, 3))
|
|
ax = axes.ravel()
|
|
|
|
ax[0].imshow(image, cmap=plt.cm.gray)
|
|
ax[0].set_title('Original image')
|
|
|
|
ax[1].imshow(binary, cmap=plt.cm.gray)
|
|
ax[1].set_title('Result')
|
|
|
|
for a in ax:
|
|
a.axis('off')
|
|
|
|
plt.show()
|