diff --git a/doc/examples/plot_label.py b/doc/examples/plot_label.py
new file mode 100644
index 00000000..8c46cb8e
--- /dev/null
+++ b/doc/examples/plot_label.py
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+"""
+===================
+Label image regions
+===================
+
+This example shows how to segment an image with image labelling. The following
+steps are applied:
+
+1. Thresholding with automatic Otsu method
+2. Close small holes with binary closing
+3. Remove artifacts touching image border
+4. Measure image regions to filter small objects
+
+"""
+
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.patches as mpatches
+
+from skimage import data
+from skimage.filter import threshold_otsu
+from skimage.segmentation import clear_border
+from skimage.morphology import label, closing, square
+from skimage.measure import regionprops
+
+
+image = data.coins()[50:-50, 50:-50]
+
+# apply threshold
+thresh = threshold_otsu(image)
+bw = closing(image > thresh, square(3))
+
+# remove artifacts connected to image border
+cleared = bw.copy()
+clear_border(cleared)
+
+# label image regions
+label_image = label(cleared)
+borders = np.logical_xor(bw, cleared)
+label_image[borders] = -1
+
+fig, ax = plt.subplots(ncols=1, nrows=1, figsize=(6, 6))
+ax.imshow(label_image, cmap='jet')
+
+for region in regionprops(label_image, ['Area', 'BoundingBox']):
+
+    # skip small images
+    if region['Area'] < 100:
+        continue
+
+    # draw rectangle around segmented coins
+    minr, minc, maxr, maxc = region['BoundingBox']
+    rect = mpatches.Rectangle((minc, minr), maxc - minc, maxr - minr,
+                              fill=False, edgecolor='red', linewidth=2)
+    ax.add_patch(rect)
+
+plt.show()