Merge pull request #2171 from rfinck/threshold_triangle

Fix threshold_triangle to work with non-integer images.

skimage/filters/tests/test_thresholding.py

@@ -320,13 +320,28 @@ def test_mean():
     assert(threshold_mean(img) == 1.)
 
 
-def test_triangle_images():
+def test_triangle_uint_images():
     assert(threshold_triangle(np.invert(data.text())) == 151)
     assert(threshold_triangle(data.text()) == 104)
     assert(threshold_triangle(data.coins()) == 80)
     assert(threshold_triangle(np.invert(data.coins())) == 175)
 
 
+def test_triangle_float_images():
+    text = data.text()
+    int_bins = text.max() - text.min() + 1
+    # Set nbins to match the uint case and threshold as float.
+    assert(round(threshold_triangle(
+        text.astype(np.float), nbins=int_bins)) == 104)
+    # Check that rescaling image to floats in unit interval is equivalent.
+    assert(round(threshold_triangle(text / 255., nbins=int_bins) * 255) == 104)
+    # Repeat for inverted image.
+    assert(round(threshold_triangle(
+        np.invert(text).astype(np.float), nbins=int_bins)) == 151)
+    assert (round(threshold_triangle(
+        np.invert(text) / 255., nbins=int_bins) * 255) == 151)
+
+
 def test_triangle_flip():
     # Depending on the skewness, the algorithm flips the histogram.
     # We check that the flip doesn't affect too much the result.

skimage/filters/thresholding.py

@@ -687,6 +687,8 @@ def threshold_triangle(image, nbins=256):
     .. [1] Zack, G. W., Rogers, W. E. and Latt, S. A., 1977,
        Automatic Measurement of Sister Chromatid Exchange Frequency,
        Journal of Histochemistry and Cytochemistry 25 (7), pp. 741-753
+    .. [2] ImageJ AutoThresholder code,
+       http://fiji.sc/wiki/index.php/Auto_Threshold
 
     Examples
     --------
@@ -695,10 +697,10 @@ def threshold_triangle(image, nbins=256):
     >>> thresh = threshold_triangle(image)
     >>> binary = image > thresh
     """
-    # nbins is ignored for interger arrays
+    # nbins is ignored for integer arrays
     # so, we recalculate the effective nbins.
     hist, bin_centers = histogram(image.ravel(), nbins)
-    nbins = bin_centers[-1] - bin_centers[0] + 1
+    nbins = len(hist)
 
     # Find peak, lowest and highest gray levels.
     arg_peak_height = np.argmax(hist)
@@ -727,14 +729,13 @@ def threshold_triangle(image, nbins=256):
     width /= norm
 
     # Maximize the length.
-    d = peak_height * arg_low_level - width * hist[arg_low_level]
-    length = peak_height * x1 - width * y1 - d
-    level = np.argmax(length) + arg_low_level
+    # The ImageJ implementation includes an additional constant when calculating
+    # the length, but here we omit it as it does not affect the location of the
+    # minimum.
+    length = peak_height * x1 - width * y1
+    arg_level = np.argmax(length) + arg_low_level
 
     if flip:
-        level = nbins - level - 1
+        arg_level = nbins - arg_level - 1
 
-    # The histogram doesn't start at zero, shift it.
-    level += bin_centers[0]
-
-    return level
+    return bin_centers[arg_level]