diff --git a/pyclustering/utils/metric.py b/pyclustering/utils/metric.py
index 52277cdf..21f9101b 100755
--- a/pyclustering/utils/metric.py
+++ b/pyclustering/utils/metric.py
@@ -328,6 +328,7 @@ def euclidean_distance_numpy(object1, object2):
     @return (double) Euclidean distance between two objects.
 
     """
+    object2 = numpy.array(object2)
     if len(object1.shape) > 1 or len(object2.shape) > 1:
         return numpy.sqrt(numpy.sum(numpy.square(object1 - object2), axis=1))
     else:
@@ -367,6 +368,7 @@ def euclidean_distance_square_numpy(object1, object2):
     @return (double) Square Euclidean distance between two objects.
 
     """
+    object2 = numpy.array(object2)
     if len(object1.shape) > 1 or len(object2.shape) > 1:
         return numpy.sum(numpy.square(object1 - object2), axis=1).T
     else:
@@ -408,6 +410,7 @@ def manhattan_distance_numpy(object1, object2):
     @return (double) Manhattan distance between two objects.
 
     """
+    object2 = numpy.array(object2)
     if len(object1.shape) > 1 or len(object2.shape) > 1:
         return numpy.sum(numpy.absolute(object1 - object2), axis=1).T
     else:
@@ -451,6 +454,7 @@ def chebyshev_distance_numpy(object1, object2):
     @return (double) Chebyshev distance between two objects.
 
     """
+    object2 = numpy.array(object2)
     if len(object1.shape) > 1 or len(object2.shape) > 1:
         return numpy.max(numpy.absolute(object1 - object2), axis=1).T
     else:
@@ -492,6 +496,7 @@ def minkowski_distance_numpy(object1, object2, degree=2):
     @return (double) Minkowski distance between two object.
 
     """
+    object2 = numpy.array(object2)
     if len(object1.shape) > 1 or len(object2.shape) > 1:
         return numpy.power(numpy.sum(numpy.power(object1 - object2, degree), axis=1), 1/degree)
     else: