Switch to Otsu instead of mean

doc/examples/segmentation/plot_thresholding.py

@@ -15,28 +15,39 @@ Thresholding is used to create a binary image from a grayscale image [1]_.
 
 ######################################################################
 # 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.
+# Otsu's method [2]_ 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.
+#
+# .. [2] http://en.wikipedia.org/wiki/Otsu's_method
 
 import matplotlib.pyplot as plt
-from skimage.filters.thresholding import threshold_mean
 from skimage import data
+from skimage.filters import threshold_otsu
+
 
 image = data.camera()
-thresh = threshold_mean(image)
+thresh = threshold_otsu(image)
 binary = image > thresh
 
-fig, axes = plt.subplots(ncols=2, figsize=(8, 3))
+fig, axes = plt.subplots(ncols=3, figsize=(8, 2.5))
 ax = axes.ravel()
+ax[0] = plt.subplot(1, 3, 1, adjustable='box-forced')
+ax[1] = plt.subplot(1, 3, 2)
+ax[2] = plt.subplot(1, 3, 3, sharex=ax[0], sharey=ax[0], adjustable='box-forced')
 
 ax[0].imshow(image, cmap=plt.cm.gray)
-ax[0].set_title('Original image')
+ax[0].set_title('Original')
+ax[0].axis('off')
 
-ax[1].imshow(binary, cmap=plt.cm.gray)
-ax[1].set_title('Result')
+ax[1].hist(image.ravel(), bins=256)
+ax[1].set_title('Histogram')
+ax[1].axvline(thresh, color='r')
 
-for a in ax:
-    a.axis('off')
+ax[2].imshow(binary, cmap=plt.cm.gray)
+ax[2].set_title('Thresholded')
+ax[2].axis('off')
 
 plt.show()