diff --git a/doc/tutorials/video/background_subtraction/background_subtraction.rst b/doc/tutorials/video/background_subtraction/background_subtraction.rst
index 3b53a26a65..0ef5ef5162 100644
--- a/doc/tutorials/video/background_subtraction/background_subtraction.rst
+++ b/doc/tutorials/video/background_subtraction/background_subtraction.rst
@@ -73,7 +73,7 @@ The results as well as the input data are shown on the screen.
     cout
     << "--------------------------------------------------------------------------"  << endl
     << "This program shows how to use background subtraction methods provided by "   << endl
-    << " OpenCV. You can process both videos (-vid) and images (-img)."              << endl														
+    << " OpenCV. You can process both videos (-vid) and images (-img)."              << endl
                                                                                      << endl
     << "Usage:"                                                                      << endl
     << "./bs {-vid <video filename>|-img <image filename>}"                          << endl
@@ -231,7 +231,7 @@ We discuss the main parts of the above code:
      Mat fgMaskMOG; //fg mask generated by MOG method
      Mat fgMaskMOG2; //fg mask fg mask generated by MOG2 method
 
-#. Two :background_subtractor:`BackgroundSubtractor <>` objects will be used to generate the foreground masks. In this example, default parameters are used, but it is also possible to declare specific parameters in the create function.   
+#. Two :background_subtractor:`BackgroundSubtractor <>` objects will be used to generate the foreground masks. In this example, default parameters are used, but it is also possible to declare specific parameters in the create function.
 
    .. code-block:: cpp
 
@@ -327,7 +327,7 @@ We discuss the main parts of the above code:
       //update the path of the current frame
       fn.assign(nextFrameFilename);
 
-   * Note that this example works only on image sequences in which the filename format is <n>.png, where n is the frame number (e.g., 7.png).
+   Note that this example works only on image sequences in which the filename format is <n>.png, where n is the frame number (e.g., 7.png).
 
 Results
 =======
@@ -342,7 +342,7 @@ Results
 
   .. image:: images/Background_Subtraction_Tutorial_Result_1.png
      :alt: Background Subtraction - Video File
-     :align: center 
+     :align: center
 
 * The video file Video_001.avi is part of the `Background Models Challenge (BMC) <http://bmc.univ-bpclermont.fr/>`_ data set and it can be downloaded from the following link `Video_001 <http://bmc.univ-bpclermont.fr/sites/default/files/videos/evaluation/Video_001.zip>`_ (about 32 MB).
 
@@ -355,8 +355,8 @@ Results
   The output of the program will look as the following:
 
   .. image:: images/Background_Subtraction_Tutorial_Result_2.png
-     :alt: Background Subtraction - Image Sequence 
-     :align: center 
+     :alt: Background Subtraction - Image Sequence
+     :align: center
 
 * The sequence of images used in this example is part of the `Background Models Challenge (BMC) <http://bmc.univ-bpclermont.fr/>`_ dataset and it can be downloaded from the following link `sequence 111 <http://bmc.univ-bpclermont.fr/sites/default/files/videos/learning/111_png.zip>`_ (about 708 MB). Please, note that this example works only on sequences in which the filename format is <n>.png, where n is the frame number (e.g., 7.png).
 
@@ -370,7 +370,7 @@ To quantitatively evaluate the results obtained, we need to:
 
 In order to save the output images, we can use :imwrite:`imwrite <>`. Adding the following code allows for saving the foreground masks.
 
-  .. code-block:: cpp 
+  .. code-block:: cpp
 
      string imageToSave = "output_MOG_" + frameNumberString + ".png";
      bool saved = imwrite(imageToSave, fgMaskMOG);
@@ -378,7 +378,7 @@ In order to save the output images, we can use :imwrite:`imwrite <>`. Adding the
        cerr << "Unable to save " << imageToSave << endl;
      }
 
-Once we have collected the result images, we can compare them with the ground truth data. There exist several publicly available sequences for background subtraction that come with ground truth data. If you decide to use the `Background Models Challenge (BMC) <http://bmc.univ-bpclermont.fr/>`_, then the result images can be used as input for the `BMC Wizard <http://bmc.univ-bpclermont.fr/?q=node/7>`_. The wizard can compute different measures about the accuracy of the results.  
+Once we have collected the result images, we can compare them with the ground truth data. There exist several publicly available sequences for background subtraction that come with ground truth data. If you decide to use the `Background Models Challenge (BMC) <http://bmc.univ-bpclermont.fr/>`_, then the result images can be used as input for the `BMC Wizard <http://bmc.univ-bpclermont.fr/?q=node/7>`_. The wizard can compute different measures about the accuracy of the results.
 
 References
 ==========