diff --git a/doc/examples/plot_circular_hough_transform.py b/doc/examples/plot_circular_hough_transform.py
new file mode 100755
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+++ b/doc/examples/plot_circular_hough_transform.py
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+#!/usr/bin/env python2
+# -*- coding: utf-8 -*-
+# Author: Francois Boulogne
+# License: GPL
+
+"""
+========================
+Circular Hough Transform
+========================
+
+
+
+"""
+
+
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.patches as mpatches
+
+from skimage import data, filter
+from skimage.transform import hough_circle
+from skimage.feature import peak_local_max
+
+# Load picture and detect edges
+image = data.coins()[0:95, 70:370]
+edges = filter.canny(filter.sobel(image), sigma=2.8)
+
+
+fig, ax = plt.subplots(ncols=1, nrows=1, figsize=(6, 6))
+ax.imshow(image, cmap=plt.cm.gray)
+
+# Detect two radii
+radii = np.array([21, 25])
+hough_res = hough_circle(edges, radii)
+
+for radius, h in zip(radii, hough_res):
+    # For each radius, keep two circles
+    maxima = peak_local_max(h, num_peaks=2)
+    for maximum in maxima:
+        center_x, center_y = maximum - radii.max()
+        circ = mpatches.Circle((center_y, center_x), radius,
+                               fill=False, edgecolor='red', linewidth=2)
+        ax.add_patch(circ)
+
+plt.show()