diff --git a/skimage/morphology/tests/test_ccomp.py b/skimage/morphology/tests/test_ccomp.py
index fb596481..c7c52d96 100644
--- a/skimage/morphology/tests/test_ccomp.py
+++ b/skimage/morphology/tests/test_ccomp.py
@@ -6,6 +6,7 @@ from warnings import catch_warnings
 from skimage._shared.utils import skimage_deprecation
 
 np.random.seed(0)
+BGL = -1
 
 
 class TestConnectedComponents:
@@ -78,7 +79,7 @@ class TestConnectedComponents:
         assert_array_equal(label(x, background=0),
                            [[-1, -1, 0],
                             [-1, -1, 0],
-                            [ 1,  1, 1]])
+                            [+1,  1, 1]])
 
     def test_background_one_region_center(self):
         x = np.array([[0, 0, 0],
@@ -101,5 +102,153 @@ class TestConnectedComponents:
         assert_array_equal(label(x, background=0, return_num=True)[1], 3)
 
 
+class TestConnectedComponents3d:
+    def setup(self):
+        self.x = np.zeros((3, 4, 5), int)
+        self.x[0] = np.array([[0, 3, 2, 1, 9],
+                              [0, 1, 9, 2, 9],
+                              [0, 1, 9, 9, 9],
+                              [3, 1, 5, 3, 0]])
+
+        self.x[1] = np.array([[3, 3, 2, 1, 9],
+                              [0, 3, 9, 2, 1],
+                              [0, 3, 3, 1, 1],
+                              [3, 1, 3, 3, 0]])
+
+        self.x[2] = np.array([[3, 3, 8, 8, 0],
+                              [2, 3, 9, 8, 8],
+                              [2, 3, 0, 8, 0],
+                              [2, 1, 0, 0, 0]])
+
+        self.labels = np.zeros((3, 4, 5), int)
+
+        self.labels[0] = np.array([[0, 1, 2, 3, 4],
+                                   [0, 5, 4, 2, 4],
+                                   [0, 5, 4, 4, 4],
+                                   [1, 5, 6, 1, 7]])
+
+        self.labels[1] = np.array([[1, 1, 2, 3, 4],
+                                   [0, 1, 4, 2, 3],
+                                   [0, 1, 1, 3, 3],
+                                   [1, 5, 1, 1, 7]])
+
+        self.labels[2] = np.array([[1, 1, 8, 8, 10],
+                                   [9, 1, 4, 8, 8],
+                                   [9, 1, 7, 8, 7],
+                                   [9, 5, 7, 7, 7]])
+
+    def test_basic(self):
+        labels = label(self.x)
+        assert_array_equal(labels, self.labels)
+
+        assert self.x[0, 0, 2] == 3, \
+            "Data was modified!"
+
+    def test_random(self):
+        x = (np.random.rand(20, 30) * 5).astype(np.int)
+
+        with catch_warnings():
+            labels = label(x)
+
+        n = labels.max()
+        for i in range(n):
+            values = x[labels == i]
+            assert np.all(values == values[0])
+
+    def test_diag(self):
+        x = np.zeros((3, 3, 3), int)
+        x[0, 2, 2] = 1
+        x[1, 1, 1] = 1
+        x[2, 0, 0] = 1
+        with catch_warnings():
+            assert_array_equal(label(x), x)
+
+    def test_4_vs_8(self):
+        x = np.zeros((2, 2, 2), int)
+        x[0, 1, 1] = 1
+        x[1, 0, 0] = 1
+        label4 = x.copy()
+        label4[1, 0, 0] = 2
+        with catch_warnings():
+            assert_array_equal(label(x, 4), label4)
+            assert_array_equal(label(x, 8), x)
+
+    def test_background(self):
+        x = np.zeros((2, 3, 3), int)
+        x[0] = np.array([[1, 0, 0],
+                         [1, 0, 0],
+                         [0, 0, 0]])
+        x[1] = np.array([[0, 0, 0],
+                         [0, 1, 5],
+                         [0, 0, 0]])
+
+        lnb = x.copy()
+        lnb[0] = np.array([[0, 1, 1],
+                           [0, 1, 1],
+                           [1, 1, 1]])
+        lnb[1] = np.array([[1, 1, 1],
+                           [1, 0, 2],
+                           [1, 1, 1]])
+        lb = x.copy()
+        lb[0] = np.array([[0,   BGL, BGL],
+                          [0,   BGL, BGL],
+                          [BGL, BGL, BGL]])
+        lb[1] = np.array([[BGL, BGL, BGL],
+                          [BGL, 0,   1],
+                          [BGL, BGL, BGL]])
+
+        with catch_warnings():
+            assert_array_equal(label(x), lnb)
+
+        assert_array_equal(label(x, background=0), lb)
+
+    def test_background_two_regions(self):
+        x = np.zeros((2, 3, 3), int)
+        x[0] = np.array([[0, 0, 6],
+                         [0, 0, 6],
+                         [5, 5, 5]])
+        x[1] = np.array([[6, 6, 0],
+                         [5, 0, 0],
+                         [0, 0, 0]])
+        lb = x.copy()
+        lb[0] = np.array([[BGL, BGL, 0],
+                          [BGL, BGL, 0],
+                          [1,   1,   1]])
+        lb[1] = np.array([[0,   0,   BGL],
+                          [1,   BGL, BGL],
+                          [BGL, BGL, BGL]])
+
+        assert_array_equal(label(x, background=0), lb)
+
+    def test_background_one_region_center(self):
+        x = np.zeros((3, 3, 3), int)
+        x[1, 1, 1] = 1
+
+        lb = np.ones_like(x) * BGL
+        lb[1, 1, 1] = 0
+
+        assert_array_equal(label(x, neighbors=4, background=0), lb)
+
+    def test_return_num(self):
+        x = np.array([[1, 0, 6],
+                      [0, 0, 6],
+                      [5, 5, 5]])
+
+        with catch_warnings():
+            assert_array_equal(label(x, return_num=True)[1], 4)
+
+        assert_array_equal(label(x, background=0, return_num=True)[1], 3)
+
+
 if __name__ == "__main__":
-    run_module_suite()
+    #run_module_suite()
+    lol = TestConnectedComponents3d()
+    lol.setup()
+    lol.test_basic()  # 1 failiure
+    lol.test_random()
+    #lol.test_diag()  # epic failiure
+    #lol.test_4_vs_8()  # label8 epic
+    #lol.test_background()
+    #lol.test_background_two_regions()
+    lol.test_background_one_region_center()
+    lol.test_return_num()