From 662ac3039ae0b5e4aecb3ca912ae9de3149945f3 Mon Sep 17 00:00:00 2001
From: Olivier Debeir <odebeir@ulb.ac.be>
Date: Thu, 18 Oct 2012 15:21:14 +0200
Subject: [PATCH] add example modal

---
 doc/examples/plot_modal_filter.py | 67 +++++++++++++++++++++++++++++++
 1 file changed, 67 insertions(+)
 create mode 100644 doc/examples/plot_modal_filter.py

diff --git a/doc/examples/plot_modal_filter.py b/doc/examples/plot_modal_filter.py
new file mode 100644
index 00000000..a66da0a1
--- /dev/null
+++ b/doc/examples/plot_modal_filter.py
@@ -0,0 +1,67 @@
+"""
+===================
+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.filter.rank import modal
+
+from skimage.morphology import label, disk
+from skimage.measure import find_contours
+
+
+image = data.coins()[50:-50, 50:-50]
+
+# apply threshold
+thresh = threshold_otsu(image)
+bw = image > thresh
+
+# label image regions
+label_image = label(bw)
+
+# filter obtained labels using model filter
+mod_label_image = modal(label_image.astype(np.uint16),disk(5))
+
+# the background is here 1
+contours = find_contours(mod_label_image==1,0, positive_orientation='low')
+
+fig, axes = plt.subplots(ncols=2, nrows=2, figsize=(6, 6))
+
+print axes
+
+ax0, ax1, ax2, ax3 = axes.ravel()
+
+ax0.imshow(bw, cmap='gray')
+ax0.set_title('Otsu threshold')
+ax1.imshow(label_image, cmap='jet')
+ax1.set_title('label image')
+ax2.imshow(mod_label_image, cmap='jet')
+ax2.set_title('filtered labels (modal)')
+ax3.imshow(image, cmap='gray')
+ax3.set_title('contour overlay')
+ax3.set_xlim((0,image.shape[1]))
+ax3.set_ylim((image.shape[0],0))
+
+
+for n, contour in enumerate(contours):
+    ax3.plot(contour[:, 1], contour[:, 0], linewidth=2)
+
+
+plt.show()
+