diff --git a/skimage/feature/peak.py b/skimage/feature/peak.py
index 4366923f..8aaf9119 100644
--- a/skimage/feature/peak.py
+++ b/skimage/feature/peak.py
@@ -19,7 +19,7 @@ def peak_local_max(image, min_distance=1, threshold_abs=None,
 
     Parameters
     ----------
-    image : ndarray of floats
+    image : ndarray
         Input image.
     min_distance : int, optional
         Minimum number of pixels separating peaks in a region of `2 *
@@ -93,6 +93,9 @@ def peak_local_max(image, min_distance=1, threshold_abs=None,
 
     """
 
+    if min_distance < 1:
+        raise ValueError("`min_disance` must greater than 0")
+
     out = np.zeros_like(image, dtype=np.bool)
 
     # In the case of labels, recursively build and return an output
diff --git a/skimage/feature/tests/test_peak.py b/skimage/feature/tests/test_peak.py
index 43a87369..e6a08eef 100644
--- a/skimage/feature/tests/test_peak.py
+++ b/skimage/feature/tests/test_peak.py
@@ -1,6 +1,6 @@
 import numpy as np
 from numpy.testing import (assert_array_almost_equal as assert_close,
-                           assert_equal)
+                           assert_equal, assert_raises)
 from scipy import ndimage as ndi
 from skimage.feature import peak
 
@@ -309,6 +309,13 @@ def test_4D():
                  [[5, 5, 5, 5], [15, 15, 15, 15]])
 
 
+def test_invalid_min_distance():
+    assert_raises(ValueError, peak.peak_local_max, np.zeros((10, 10)),
+                  min_distance=0)
+    assert_raises(ValueError, peak.peak_local_max, np.zeros((10, 10)),
+                  min_distance=-1)
+
+
 if __name__ == '__main__':
     from numpy import testing
     testing.run_module_suite()