added adaptive threshold

doc/examples/plot_thresholding.py

@@ -0,0 +1,56 @@
+"""
+============
+Thresholding
+============
+
+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.
+
+Additionnally an adaptive thresholding is applied. Also known as local or
+dynamic thresholding where the the threshold value is the weighted mean for the
+local neighborhood of a pixel subtracted by a constant.
+
+.. [1] http://en.wikipedia.org/wiki/Otsu's_method
+
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+from skimage.data import camera
+from skimage.filter import threshold_otsu, adaptive_threshold
+
+
+image = camera()
+thresh = threshold_otsu(image)
+otsu_binary = image > thresh
+adaptive_binary = np.invert(adaptive_threshold(image, 9, 5))
+
+plt.figure(figsize=(8, 2.5))
+plt.subplot(2, 2, 1)
+plt.imshow(image, cmap=plt.cm.gray)
+plt.title('Original')
+plt.axis('off')
+
+plt.subplot(2, 2, 2, aspect='equal')
+plt.hist(image)
+plt.title('Histogram')
+plt.axvline(thresh, color='r')
+
+plt.subplot(2, 2, 3)
+plt.imshow(otsu_binary, cmap=plt.cm.gray)
+plt.title('Thresholded with Otsu')
+plt.axis('off')
+
+plt.subplot(2, 2, 4)
+plt.imshow(adaptive_binary, cmap=plt.cm.gray)
+plt.title('Adaptively thresholded')
+plt.axis('off')
+
+plt.show()
+
+