Merge remote-tracking branch 'origin/2.4' into merge-2.4
Conflicts: CMakeLists.txt cmake/OpenCVDetectCUDA.cmake doc/tutorials/features2d/feature_flann_matcher/feature_flann_matcher.rst modules/core/src/cmdparser.cpp modules/gpu/CMakeLists.txt modules/gpu/doc/introduction.rst modules/gpu/perf/perf_video.cpp modules/highgui/doc/reading_and_writing_images_and_video.rst modules/ocl/src/cl_context.cpp modules/video/include/opencv2/video/background_segm.hpp samples/cpp/image_sequence.cpp samples/cpp/tutorial_code/ImgTrans/HoughCircle_Demo.cpp samples/python/chessboard.py samples/python/cvutils.py samples/python/demhist.py samples/python/dft.py samples/python/distrans.py samples/python/edge.py samples/python/ffilldemo.py samples/python/fitellipse.py samples/python/houghlines.py samples/python/inpaint.py samples/python/logpolar.py samples/python/morphology.py samples/python/numpy_array.py samples/python/watershed.py
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@@ -86,7 +86,7 @@ Code
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* Applies the *Canny Detector* and generates a **mask** (bright lines representing the edges on a black background).
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* Applies the mask obtained on the original image and display it in a window.
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#. The tutorial code's is shown lines below. You can also download it from `here <http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp>`_
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#. The tutorial code's is shown lines below. You can also download it from `here <https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp>`_
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.. code-block:: cpp
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@@ -47,7 +47,7 @@ Code
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The user chooses either option by pressing 'c' (constant) or 'r' (replicate)
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* The program finishes when the user presses 'ESC'
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#. The tutorial code's is shown lines below. You can also download it from `here <http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/tutorial_code/ImgTrans/copyMakeBorder_demo.cpp>`_
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#. The tutorial code's is shown lines below. You can also download it from `here <https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/copyMakeBorder_demo.cpp>`_
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.. code-block:: cpp
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* The filter output (with each kernel) will be shown during 500 milliseconds
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#. The tutorial code's is shown lines below. You can also download it from `here <http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/tutorial_code/ImgTrans/filter2D_demo.cpp>`_
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#. The tutorial code's is shown lines below. You can also download it from `here <https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/filter2D_demo.cpp>`_
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.. code-block:: cpp
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* Display the detected circle in a window.
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.. |TutorialHoughCirclesSimpleDownload| replace:: here
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.. _TutorialHoughCirclesSimpleDownload: http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/houghcircles.cpp
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.. _TutorialHoughCirclesSimpleDownload: https://github.com/Itseez/opencv/tree/master/samples/cpp/houghcircles.cpp
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.. |TutorialHoughCirclesFancyDownload| replace:: here
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.. _TutorialHoughCirclesFancyDownload: http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/tutorial_code/ImgTrans/HoughCircle_Demo.cpp
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.. _TutorialHoughCirclesFancyDownload: https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/HoughCircle_Demo.cpp
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#. The sample code that we will explain can be downloaded from |TutorialHoughCirclesSimpleDownload|_. A slightly fancier version (which shows both Hough standard and probabilistic with trackbars for changing the threshold values) can be found |TutorialHoughCirclesFancyDownload|_.
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@@ -89,9 +89,9 @@ Code
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======
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.. |TutorialHoughLinesSimpleDownload| replace:: here
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.. _TutorialHoughLinesSimpleDownload: http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/houghlines.cpp
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.. _TutorialHoughLinesSimpleDownload: https://github.com/Itseez/opencv/tree/master/samples/cpp/houghlines.cpp
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.. |TutorialHoughLinesFancyDownload| replace:: here
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.. _TutorialHoughLinesFancyDownload: http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/tutorial_code/ImgTrans/HoughLines_Demo.cpp
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.. _TutorialHoughLinesFancyDownload: https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/HoughLines_Demo.cpp
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#. **What does this program do?**
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* Applies a Laplacian operator to the grayscale image and stores the output image
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* Display the result in a window
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#. The tutorial code's is shown lines below. You can also download it from `here <http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp>`_
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#. The tutorial code's is shown lines below. You can also download it from `here <https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp>`_
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.. code-block:: cpp
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* Each second, apply 1 of 4 different remapping processes to the image and display them indefinitely in a window.
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* Wait for the user to exit the program
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#. The tutorial code's is shown lines below. You can also download it from `here <http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp>`_
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#. The tutorial code's is shown lines below. You can also download it from `here <https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp>`_
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.. code-block:: cpp
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@@ -121,7 +121,7 @@ Code
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* Applies the *Sobel Operator* and generates as output an image with the detected *edges* bright on a darker background.
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#. The tutorial code's is shown lines below. You can also download it from `here <http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp>`_
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#. The tutorial code's is shown lines below. You can also download it from `here <https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/Sobel_Demo.cpp>`_
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.. code-block:: cpp
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@@ -71,7 +71,7 @@ How do we get an Affine Transformation?
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a. We know both :math:`X` and `T` and we also know that they are related. Then our job is to find :math:`M`
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b. We know :math:`M` and :math:'X`. To obtain :math:`T` we only need to apply :math:`T = M \cdot X`. Our information for :math:`M` may be explicit (i.e. have the 2-by-3 matrix) or it can come as a geometric relation between points.
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b. We know :math:`M` and :math:`X`. To obtain :math:`T` we only need to apply :math:`T = M \cdot X`. Our information for :math:`M` may be explicit (i.e. have the 2-by-3 matrix) or it can come as a geometric relation between points.
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2. Let's explain a little bit better (b). Since :math:`M` relates 02 images, we can analyze the simplest case in which it relates three points in both images. Look at the figure below:
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@@ -93,7 +93,7 @@ Code
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* Applies a Rotation to the image after being transformed. This rotation is with respect to the image center
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* Waits until the user exits the program
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#. The tutorial code's is shown lines below. You can also download it from `here <http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/tutorial_code/ImgTrans/Geometric_Transforms_Demo.cpp>`_
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#. The tutorial code's is shown lines below. You can also download it from `here <https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/Geometric_Transforms_Demo.cpp>`_
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.. code-block:: cpp
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