Added sections to gallery of examples

Modified travis_script.sh to account for the new structure of the gallery

Added README.txt files in directories of gallery examples

Fixed references to gallery images in user guide pages

Fixed broken links

doc/examples/edges/plot_canny.py

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+"""
+===================
+Canny edge detector
+===================
+
+The Canny filter is a multi-stage edge detector. It uses a filter based on the
+derivative of a Gaussian in order to compute the intensity of the gradients.The
+Gaussian reduces the effect of noise present in the image. Then, potential
+edges are thinned down to 1-pixel curves by removing non-maximum pixels of the
+gradient magnitude. Finally, edge pixels are kept or removed using hysteresis
+thresholding on the gradient magnitude.
+
+The Canny has three adjustable parameters: the width of the Gaussian (the
+noisier the image, the greater the width), and the low and high threshold for
+the hysteresis thresholding.
+
+"""
+import numpy as np
+import matplotlib.pyplot as plt
+from scipy import ndimage as ndi
+
+from skimage import feature
+
+
+# Generate noisy image of a square
+im = np.zeros((128, 128))
+im[32:-32, 32:-32] = 1
+
+im = ndi.rotate(im, 15, mode='constant')
+im = ndi.gaussian_filter(im, 4)
+im += 0.2 * np.random.random(im.shape)
+
+# Compute the Canny filter for two values of sigma
+edges1 = feature.canny(im)
+edges2 = feature.canny(im, sigma=3)
+
+# display results
+fig, (ax1, ax2, ax3) = plt.subplots(nrows=1, ncols=3, figsize=(8, 3), sharex=True, sharey=True)
+
+ax1.imshow(im, cmap=plt.cm.jet)
+ax1.axis('off')
+ax1.set_title('noisy image', fontsize=20)
+
+ax2.imshow(edges1, cmap=plt.cm.gray)
+ax2.axis('off')
+ax2.set_title('Canny filter, $\sigma=1$', fontsize=20)
+
+ax3.imshow(edges2, cmap=plt.cm.gray)
+ax3.axis('off')
+ax3.set_title('Canny filter, $\sigma=3$', fontsize=20)
+
+fig.subplots_adjust(wspace=0.02, hspace=0.02, top=0.9,
+                    bottom=0.02, left=0.02, right=0.98)
+
+plt.show()