diff --git a/skimage/filter/rank/_core16.pyx b/skimage/filter/rank/_core16.pyx
index 36bc500d..0c7a7a82 100644
--- a/skimage/filter/rank/_core16.pyx
+++ b/skimage/filter/rank/_core16.pyx
@@ -101,16 +101,16 @@ cdef void _core16(dtype_t kernel(Py_ssize_t *, float, dtype_t,
     # build attack and release borders
     # by using difference along axis
     t = np.hstack((selem, np.zeros((selem.shape[0], 1))))
-    t_e = np.diff(t, axis=1) == -1
+    t_e = np.diff(t, axis=1) < 0
 
     t = np.hstack((np.zeros((selem.shape[0], 1)), selem))
-    t_w = np.diff(t, axis=1) == 1
+    t_w = np.diff(t, axis=1) > 0
 
     t = np.vstack((selem, np.zeros((1, selem.shape[1]))))
-    t_s = np.diff(t, axis=0) == -1
+    t_s = np.diff(t, axis=0) < 0
 
     t = np.vstack((np.zeros((1, selem.shape[1])), selem))
-    t_n = np.diff(t, axis=0) == 1
+    t_n = np.diff(t, axis=0) > 0
 
     num_se_n = num_se_s = num_se_e = num_se_w = 0
 
diff --git a/skimage/filter/rank/_core8.pyx b/skimage/filter/rank/_core8.pyx
index eca47891..79ae9bbf 100644
--- a/skimage/filter/rank/_core8.pyx
+++ b/skimage/filter/rank/_core8.pyx
@@ -104,16 +104,16 @@ cdef void _core8(dtype_t kernel(Py_ssize_t *, float, dtype_t, float,
     # build attack and release borders
     # by using difference along axis
     t = np.hstack((selem, np.zeros((selem.shape[0], 1))))
-    t_e = np.diff(t, axis=1) == -1
+    t_e = np.diff(t, axis=1) < 0
 
     t = np.hstack((np.zeros((selem.shape[0], 1)), selem))
-    t_w = np.diff(t, axis=1) == 1
+    t_w = np.diff(t, axis=1) > 0
 
     t = np.vstack((selem, np.zeros((1, selem.shape[1]))))
-    t_s = np.diff(t, axis=0) == -1
+    t_s = np.diff(t, axis=0) < 0
 
     t = np.vstack((np.zeros((1, selem.shape[1])), selem))
-    t_n = np.diff(t, axis=0) == 1
+    t_n = np.diff(t, axis=0) > 0
 
     num_se_n = num_se_s = num_se_e = num_se_w = 0
 
diff --git a/skimage/filter/rank/bilateral_rank.pyx b/skimage/filter/rank/bilateral_rank.pyx
index 04f6cb35..e2a1fcf3 100644
--- a/skimage/filter/rank/bilateral_rank.pyx
+++ b/skimage/filter/rank/bilateral_rank.pyx
@@ -36,7 +36,7 @@ __all__ = ['bilateral_mean', 'bilateral_pop']
 
 
 def _apply(func8, func16, image, selem, out, mask, shift_x, shift_y, s0, s1):
-    selem = img_as_ubyte(selem)
+    selem = img_as_ubyte(selem > 0)
     image = np.ascontiguousarray(image)
 
     if mask is None:
diff --git a/skimage/filter/rank/percentile_rank.pyx b/skimage/filter/rank/percentile_rank.pyx
index 7deae623..9db81bcc 100644
--- a/skimage/filter/rank/percentile_rank.pyx
+++ b/skimage/filter/rank/percentile_rank.pyx
@@ -35,7 +35,7 @@ __all__ = ['percentile_autolevel', 'percentile_gradient',
 
 
 def _apply(func8, func16, image, selem, out, mask, shift_x, shift_y, p0, p1):
-    selem = img_as_ubyte(selem)
+    selem = img_as_ubyte(selem > 0)
     image = np.ascontiguousarray(image)
 
     if mask is None:
diff --git a/skimage/filter/rank/rank.pyx b/skimage/filter/rank/rank.pyx
index 5380363a..2ef5484e 100644
--- a/skimage/filter/rank/rank.pyx
+++ b/skimage/filter/rank/rank.pyx
@@ -28,7 +28,7 @@ __all__ = ['autolevel', 'bottomhat', 'equalize', 'gradient', 'maximum', 'mean',
 
 
 def _apply(func8, func16, image, selem, out, mask, shift_x, shift_y):
-    selem = img_as_ubyte(selem)
+    selem = img_as_ubyte(selem > 0)
     image = np.ascontiguousarray(image)
 
     if mask is None:
diff --git a/skimage/filter/rank/tests/test_rank.py b/skimage/filter/rank/tests/test_rank.py
index 43ff030f..62363675 100644
--- a/skimage/filter/rank/tests/test_rank.py
+++ b/skimage/filter/rank/tests/test_rank.py
@@ -376,5 +376,25 @@ def test_entropy():
     assert(np.max(rank.entropy(data, selem)) == 12000)
 
 
+def test_selem_dtypes():
+
+    image = np.zeros((5, 5), dtype=np.uint8)
+    out = np.zeros_like(image)
+    mask = np.ones_like(image, dtype=np.uint8)
+    image[2, 2] = 255
+    image[2, 3] = 128
+    image[1, 2] = 16
+
+    for dtype in (np.uint8, np.uint16, np.int32, np.int64,
+                  np.float32, np.float64):
+        elem = np.array([[0, 0, 0], [0, 1, 0], [0, 0, 0]], dtype=dtype)
+        rank.mean(image=image, selem=elem, out=out, mask=mask,
+                  shift_x=0, shift_y=0)
+        assert_array_equal(image, out)
+        rank.percentile_mean(image=image, selem=elem, out=out, mask=mask,
+                             shift_x=0, shift_y=0)
+        assert_array_equal(image, out)
+
+
 if __name__ == "__main__":
     run_module_suite()