Tutorial Hit-or-Miss

doc/tutorials/imgproc/hitOrMiss/hitOrMiss.markdown

@@ -1,22 +1,23 @@
 Hit-or-Miss {#tutorial_hitOrMiss}
 =================================
 
+@prev_tutorial{tutorial_opening_closing_hats}
+@next_tutorial{tutorial_morph_lines_detection}
+
 Goal
 ----
 
 In this tutorial you will learn how to find a given configuration or pattern in a binary image by using the Hit-or-Miss transform (also known as Hit-and-Miss transform).
 This transform is also the basis of more advanced morphological operations such as thinning or pruning.
 
-We will use the OpenCV function @ref cv::morphologyEx.
-
-
+We will use the OpenCV function **morphologyEx()** .
 
 Hit-or-Miss theory
 -------------------
 
 Morphological operators process images based on their shape. These operators apply one or more *structuring elements* to an input image to obtain the output image.
 The two basic morphological operations are the *erosion* and the *dilation*. The combination of these two operations generate advanced morphological transformations such as *opening*, *closing*, or *top-hat* transform.
-To know more about these and other basic morphological operations refer to previous tutorials @ref tutorial_erosion_dilatation "here" and @ref tutorial_opening_closing_hats "here".
+To know more about these and other basic morphological operations refer to previous tutorials (@ref tutorial_erosion_dilatation "Eroding and Dilating") and (@ref tutorial_opening_closing_hats "More Morphology Transformations").
 
 The Hit-or-Miss transformation is useful to find patterns in binary images. In particular, it finds those pixels whose neighbourhood matches the shape of a first structuring element \f$B_1\f$
 while not matching the shape of a second structuring element \f$B_2\f$ at the same time. Mathematically, the operation applied to an image \f$A\f$ can be expressed as follows:
@@ -43,11 +44,27 @@ You can see that the pattern is found in just one location within the image.
 Code
 ----
 
-The code corresponding to the previous example is shown below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/HitMiss.cpp)
-@include samples/cpp/tutorial_code/ImgProc/HitMiss.cpp
+The code corresponding to the previous example is shown below.
 
-As you can see, it is as simple as using the function @ref cv::morphologyEx with the operation type @ref cv::MORPH_HITMISS and the chosen kernel.
+@add_toggle_cpp
+You can also download it from
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgProc/HitMiss/HitMiss.cpp)
+@include samples/cpp/tutorial_code/ImgProc/HitMiss/HitMiss.cpp
+@end_toggle
+
+@add_toggle_java
+You can also download it from
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgProc/HitMiss/HitMiss.java)
+@include samples/java/tutorial_code/ImgProc/HitMiss/HitMiss.java
+@end_toggle
+
+@add_toggle_python
+You can also download it from
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/imgProc/HitMiss/hit_miss.py)
+@include samples/python/tutorial_code/imgProc/HitMiss/hit_miss.py
+@end_toggle
+
+As you can see, it is as simple as using the function **morphologyEx()** with the operation type **MORPH_HITMISS** and the chosen kernel.
 
 Other examples
 --------------

doc/tutorials/imgproc/table_of_content_imgproc.markdown

@@ -29,7 +29,9 @@ In this section you will learn about the image processing (manipulation) functio
 
     Here we investigate different morphology operators
 
--	@subpage tutorial_hitOrMiss
+-   @subpage tutorial_hitOrMiss
+
+    *Languages:* C++, Java, Python
 
     *Compatibility:* \> OpenCV 2.4