diff --git a/skimage/segmentation/random_walker_segmentation.py b/skimage/segmentation/random_walker_segmentation.py
index c66e9c6f..d722569b 100644
--- a/skimage/segmentation/random_walker_segmentation.py
+++ b/skimage/segmentation/random_walker_segmentation.py
@@ -9,7 +9,6 @@ significantly the performance.
 """
 
 import warnings
-from numbers import Number
 import numpy as np
 from scipy import sparse, ndimage
 
@@ -396,10 +395,6 @@ def random_walker(data, labels, beta=130, mode='bf', tol=1.e-3, copy=True,
     if spacing is None:
         spacing = np.asarray((1.,) * 3)
     elif len(spacing) == len(dims):
-        for i in spacing:
-            if not isinstance(i, Number):
-                raise ValueError('Input `spacing` contained %s, which is not '
-                                 'a number.' % (i))
         if len(spacing) == 2:  # Need a dummy spacing for singleton 3rd dim
             spacing = np.r_[spacing, 1.]
         else:                  # Convert to array
diff --git a/skimage/segmentation/tests/test_random_walker.py b/skimage/segmentation/tests/test_random_walker.py
index a7318daa..9d30473b 100644
--- a/skimage/segmentation/tests/test_random_walker.py
+++ b/skimage/segmentation/tests/test_random_walker.py
@@ -305,10 +305,6 @@ def test_bad_inputs():
     np.testing.assert_raises(ValueError,
                              random_walker, img, labels, spacing=(1,))
 
-    # Spacing contains unacceptable information
-    np.testing.assert_raises(
-        ValueError, random_walker, img, labels, spacing=(1, 'chickens'))
-
 
 if __name__ == '__main__':
     np.testing.run_module_suite()