check if input for canny is 2d array, test for error raise.

scikits/image/filter/canny.py

@@ -111,6 +111,10 @@ def canny(image, sigma, low_threshold, high_threshold, mask=None):
     # mask by one and then mask the output. We also mask out the border points
     # because who knows what lies beyond the edge of the image?
     #
+
+    if image.ndim!=2:
+        raise TypeError("The input 'image' must be a two dimensional array.")
+
     if mask is None:
         mask = np.ones(image.shape, dtype=bool)
     fsmooth = lambda x: gaussian_filter(x, sigma, mode='constant')

scikits/image/filter/tests/test_canny.py

@@ -56,3 +56,6 @@ class TestCanny(unittest.TestCase):
         point_count = np.sum(result)
         self.assertTrue(point_count > 1200)
         self.assertTrue(point_count < 1600)
+
+    def test_image_shape(self):
+        self.assertRaises(TypeError,F.canny,np.zeros((20, 20, 20)), 4, 0, 0)