diff --git a/CONTRIBUTORS.txt b/CONTRIBUTORS.txt
index 5961407d..735bffa9 100644
--- a/CONTRIBUTORS.txt
+++ b/CONTRIBUTORS.txt
@@ -108,3 +108,6 @@
   Adaptive thresholding
   Implementation of Matlab's `regionprops`
   Estimation of geometric transformation parameters
+  
+- Pavel Campr
+  Fixes and tests for Histograms of Oriented Gradients.
diff --git a/skimage/feature/_hog.py b/skimage/feature/_hog.py
index 3bd849ab..ce7db462 100644
--- a/skimage/feature/_hog.py
+++ b/skimage/feature/_hog.py
@@ -181,4 +181,4 @@ def hog(image, orientations=9, pixels_per_cell=(8, 8),
     if visualise:
         return normalised_blocks.ravel(), hog_image
     else:
-        return normalised_blocks.ravel()
\ No newline at end of file
+        return normalised_blocks.ravel()
diff --git a/skimage/feature/tests/test_hog.py b/skimage/feature/tests/test_hog.py
index 8cf45fb8..c9449028 100644
--- a/skimage/feature/tests/test_hog.py
+++ b/skimage/feature/tests/test_hog.py
@@ -32,8 +32,6 @@ def test_hog_basic_orientations_and_data_types():
     #  4) verify that all results are equal where expected
     #  5) verify that computed feature vector is as expected
     #  6) repeat the scenario for 90, 180 and 270 degrees rotated images
-    #
-    # author: Pavel Campr
 
     # size of testing image
     width = height = 35
@@ -99,8 +97,6 @@ def test_hog_orientations_circle():
     #  3) verify that the resulting feature vector contains uniformly distributed values for all orientations,
     #     i.e. no orientation is lost or emphasized
     #  4) repeat the scenario for other 'orientations' option
-    #
-    # author: Pavel Campr
 
     # size of testing image
     width = height = 100