diff --git a/doc/examples/plot_join_segmentations.py b/doc/examples/plot_join_segmentations.py
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+"""
+==========================================
+Find the intersection of two segmentations
+==========================================
+
+When segmenting an image, you may want to combine multiple alternative
+segmentations. The `skimage.segmentation.join_segmentations` function
+computes the join of two segmentations, in which a pixel is placed in
+the same segment if and only if it is in the same segment in _both_
+segmentations.
+"""
+
+import numpy as np
+from scipy import ndimage as nd
+import matplotlib.pyplot as plt
+import matplotlib as mpl
+
+from skimage.filter import sobel
+from skimage.segmentation import slic, join_segmentations
+from skimage.morphology import watershed
+
+from skimage import data
+
+coins = data.coins()
+
+# make segmentation using edge-detection and watershed
+edges = sobel(coins)
+markers = np.zeros_like(coins)
+foreground, background = 1, 2
+markers[coins < 30] = background
+markers[coins > 150] = foreground
+
+ws = watershed(edges, markers)
+seg1 = nd.label(ws == foreground)[0]
+
+# make segmentation using SLIC superpixels
+
+# make the RGB equivalent of `coins`
+coins_colour = np.tile(coins[..., np.newaxis], (1, 1, 3))
+seg2 = slic(coins_colour, max_iter=20, sigma=0, convert2lab=False)
+
+# combine the two
+segj = join_segmentations(seg1, seg2)
+
+### Display the result ###
+
+# make a random colormap for a set number of values
+def random_cmap(im):
+    np.random.seed(9)
+    cmap_array = np.concatenate(
+        (np.zeros((1, 3)), np.random.rand(np.ceil(im.max()), 3)))
+    return mpl.colors.ListedColormap(cmap_array)
+
+# show the segmentations
+fig, axes = plt.subplots(ncols=4, figsize=(9, 2.5))
+axes[0].imshow(coins, cmap=plt.cm.gray, interpolation='nearest')
+axes[0].set_title('Image')
+axes[1].imshow(seg1, cmap=random_cmap(seg1), interpolation='nearest')
+axes[1].set_title('Sobel+Watershed')
+axes[2].imshow(seg2, cmap=random_cmap(seg2), interpolation='nearest')
+axes[2].set_title('SLIC superpixels')
+axes[3].imshow(segj, cmap=random_cmap(segj), interpolation='nearest')
+axes[3].set_title('Join')
+
+for ax in axes:
+    ax.axis('off')
+plt.subplots_adjust(hspace=0.01, wspace=0.01, top=1, bottom=0, left=0, right=1)
+plt.show()