move tutorial to imgproc and example to ImgTrans

doc/tutorials/imgproc/generalized_hough_ballard_guil/generalized_hough_ballard_guil.markdown

@@ -3,7 +3,8 @@ Object detection with Generalized Ballard and Guil Hough Transform {#tutorial_ge
 
 @tableofcontents
 
-@prev_tutorial{tutorial_traincascade}
+@prev_tutorial{tutorial_hough_circle}
+@next_tutorial{tutorial_remap}
 
 Goal
 ----
@@ -39,14 +40,14 @@ Example
 ### Code
 
 The complete code for this tutorial is shown below.
-@include samples/cpp/tutorial_code/objectDetection/generalizedHoughTransform.cpp
+@include samples/cpp/tutorial_code/ImgTrans/generalizedHoughTransform.cpp
 
 Explanation
 -----------
 
 ### Load image, template and setup variables
 
-@snippet samples/cpp/tutorial_code/objectDetection/generalizedHoughTransform.cpp generalized-hough-transform-load-and-setup
+@snippet samples/cpp/tutorial_code/ImgTrans/generalizedHoughTransform.cpp generalized-hough-transform-load-and-setup
 
 The position vectors will contain the matches the detectors will find.
 Every entry contains four floating point values:
@@ -61,19 +62,19 @@ An example could look as follows: `[200, 100, 0.9, 120]`
 
 ### Setup parameters
 
-@snippet samples/cpp/tutorial_code/objectDetection/generalizedHoughTransform.cpp generalized-hough-transform-setup-parameters
+@snippet samples/cpp/tutorial_code/ImgTrans/generalizedHoughTransform.cpp generalized-hough-transform-setup-parameters
 
 Finding the optimal values can end up in trial and error and depends on many factors, such as the image resolution.
 
 ### Run detection
 
-@snippet samples/cpp/tutorial_code/objectDetection/generalizedHoughTransform.cpp generalized-hough-transform-run
+@snippet samples/cpp/tutorial_code/ImgTrans/generalizedHoughTransform.cpp generalized-hough-transform-run
 
 As mentioned above, this step will take some time, especially with larger images and when using Guil.
 
 ### Draw results and show image
 
-@snippet samples/cpp/tutorial_code/objectDetection/generalizedHoughTransform.cpp generalized-hough-transform-draw-results
+@snippet samples/cpp/tutorial_code/ImgTrans/generalizedHoughTransform.cpp generalized-hough-transform-draw-results
 
 Result
 ------

doc/tutorials/imgproc/imgtrans/hough_circle/hough_circle.markdown

@@ -2,7 +2,7 @@ Hough Circle Transform {#tutorial_hough_circle}
 ======================
 
 @prev_tutorial{tutorial_hough_lines}
-@next_tutorial{tutorial_remap}
+@next_tutorial{tutorial_generalized_hough_ballard_guil}
 
 Goal
 ----

doc/tutorials/imgproc/imgtrans/remap/remap.markdown

@@ -1,7 +1,7 @@
 Remapping {#tutorial_remap}
 =========
 
-@prev_tutorial{tutorial_hough_circle}
+@prev_tutorial{tutorial_generalized_hough_ballard_guil}
 @next_tutorial{tutorial_warp_affine}
 
 Goal

doc/tutorials/imgproc/table_of_content_imgproc.markdown

@@ -173,6 +173,16 @@ In this section you will learn about the image processing (manipulation) functio
 
     Where we learn how to detect circles
 
+-   @subpage tutorial_generalized_hough_ballard_guil
+
+    *Languages:* C++
+
+    *Compatibility:* \>= OpenCV 3.4
+
+    *Author:* Markus Heck
+
+    Detect an object in a picture with the help of GeneralizedHoughBallard and GeneralizedHoughGuil.
+
 -   @subpage tutorial_remap
 
     *Languages:* C++, Java, Python

doc/tutorials/objdetect/table_of_content_objdetect.markdown

@@ -16,13 +16,3 @@ Ever wondered how your digital camera detects peoples and faces? Look here to fi
 -   @subpage tutorial_traincascade
 
     This tutorial describes _opencv_traincascade_ application and its parameters.
-
--   @subpage tutorial_generalized_hough_ballard_guil
-
-    *Languages:* C++
-
-    *Compatibility:* \>= OpenCV 3.4
-
-    *Author:* Markus Heck
-
-    Detect an object in a picture with the help of GeneralizedHoughBallard and GeneralizedHoughGuil.

doc/tutorials/objdetect/traincascade.markdown

@@ -2,7 +2,6 @@ Cascade Classifier Training {#tutorial_traincascade}
 ===========================
 
 @prev_tutorial{tutorial_cascade_classifier}
-@next_tutorial{tutorial_generalized_hough_ballard_guil}
 
 
 Introduction