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/features_detection/plot_brief.py

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+"""
+=======================
+BRIEF binary descriptor
+=======================
+
+This example demonstrates the BRIEF binary description algorithm.
+
+The descriptor consists of relatively few bits and can be computed using
+a set of intensity difference tests. The short binary descriptor results
+in low memory footprint and very efficient matching based on the Hamming
+distance metric.
+
+BRIEF does not provide rotation-invariance. Scale-invariance can be achieved by
+detecting and extracting features at different scales.
+
+"""
+from skimage import data
+from skimage import transform as tf
+from skimage.feature import (match_descriptors, corner_peaks, corner_harris,
+                             plot_matches, BRIEF)
+from skimage.color import rgb2gray
+import matplotlib.pyplot as plt
+
+
+img1 = rgb2gray(data.astronaut())
+tform = tf.AffineTransform(scale=(1.2, 1.2), translation=(0, -100))
+img2 = tf.warp(img1, tform)
+img3 = tf.rotate(img1, 25)
+
+keypoints1 = corner_peaks(corner_harris(img1), min_distance=5)
+keypoints2 = corner_peaks(corner_harris(img2), min_distance=5)
+keypoints3 = corner_peaks(corner_harris(img3), min_distance=5)
+
+extractor = BRIEF()
+
+extractor.extract(img1, keypoints1)
+keypoints1 = keypoints1[extractor.mask]
+descriptors1 = extractor.descriptors
+
+extractor.extract(img2, keypoints2)
+keypoints2 = keypoints2[extractor.mask]
+descriptors2 = extractor.descriptors
+
+extractor.extract(img3, keypoints3)
+keypoints3 = keypoints3[extractor.mask]
+descriptors3 = extractor.descriptors
+
+matches12 = match_descriptors(descriptors1, descriptors2, cross_check=True)
+matches13 = match_descriptors(descriptors1, descriptors3, cross_check=True)
+
+fig, ax = plt.subplots(nrows=2, ncols=1)
+
+plt.gray()
+
+plot_matches(ax[0], img1, img2, keypoints1, keypoints2, matches12)
+ax[0].axis('off')
+
+plot_matches(ax[1], img1, img3, keypoints1, keypoints3, matches13)
+ax[1].axis('off')
+
+plt.show()