ThresholdingΒΆ

Thresholding is used to create a binary image. This example uses Otsu’s method to calculate the threshold value.

Otsu’s method 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.

[1]http://en.wikipedia.org/wiki/Otsu’s_method
../../_images/plot_otsu_1.png
import matplotlib
import matplotlib.pyplot as plt

from skimage.data import camera
from skimage.filters import threshold_otsu


matplotlib.rcParams['font.size'] = 9


image = camera()
thresh = threshold_otsu(image)
binary = image > thresh

#fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(8, 2.5))
fig = plt.figure(figsize=(8, 2.5))
ax1 = plt.subplot(1, 3, 1, adjustable='box-forced')
ax2 = plt.subplot(1, 3, 2)
ax3 = plt.subplot(1, 3, 3, sharex=ax1, sharey=ax1, adjustable='box-forced')

ax1.imshow(image, cmap=plt.cm.gray)
ax1.set_title('Original')
ax1.axis('off')

ax2.hist(image)
ax2.set_title('Histogram')
ax2.axvline(thresh, color='r')

ax3.imshow(binary, cmap=plt.cm.gray)
ax3.set_title('Thresholded')
ax3.axis('off')

plt.show()

Python source code: download (generated using skimage 0.12.3)

IPython Notebook: download (generated using skimage 0.12.3)