Merge pull request #1907 from OrkoHunter/threshold_adaptive_block_size

Modify threshold_adaptive

doc/examples/segmentation/plot_threshold_adaptive.py

@@ -26,7 +26,7 @@ image = data.page()
 global_thresh = threshold_otsu(image)
 binary_global = image > global_thresh
 
-block_size = 40
+block_size = 35
 binary_adaptive = threshold_adaptive(image, block_size, offset=10)
 
 fig, axes = plt.subplots(nrows=3, figsize=(7, 8))

skimage/filters/tests/test_thresholding.py

@@ -203,6 +203,11 @@ def test_yen_coins_image_as_float():
     assert 0.43 < threshold_yen(coins) < 0.44
 
 
+def test_adaptive_even_block_size_error():
+    img = data.camera()
+    assert_raises(ValueError, threshold_adaptive, img, block_size=4)
+
+
 def test_isodata_camera_image():
     camera = skimage.img_as_ubyte(data.camera())
 

skimage/filters/thresholding.py

@@ -25,7 +25,7 @@ def threshold_adaptive(image, block_size, method='gaussian', offset=0,
     image : (N, M) ndarray
         Input image.
     block_size : int
-        Uneven size of pixel neighborhood which is used to calculate the
+        Odd size of pixel neighborhood which is used to calculate the
         threshold value (e.g. 3, 5, 7, ..., 21, ...).
     method : {'generic', 'gaussian', 'mean', 'median'}, optional
         Method used to determine adaptive threshold for local neighbourhood in
@@ -68,6 +68,9 @@ def threshold_adaptive(image, block_size, method='gaussian', offset=0,
     >>> func = lambda arr: arr.mean()
     >>> binary_image2 = threshold_adaptive(image, 15, 'generic', param=func)
     """
+    if block_size % 2 == 0:
+        raise ValueError("The kwarg ``block_size`` must be odd! Given "
+                         "``block_size`` {0} is even.".format(block_size))
     assert_nD(image, 2)
     thresh_image = np.zeros(image.shape, 'double')
     if method == 'generic':