Merge remote-tracking branch 'origin/2.4' into merge-2.4

Conflicts:
	modules/core/include/opencv2/core/version.hpp
	modules/core/src/out.cpp
	modules/cudaimgproc/test/test_hough.cpp
	modules/gpu/doc/introduction.rst
	modules/gpu/perf/perf_imgproc.cpp
	modules/gpu/src/generalized_hough.cpp
	modules/nonfree/perf/perf_main.cpp

modules/cuda/doc/introduction.rst

@@ -45,7 +45,7 @@ Utilizing Multiple GPUs
 -----------------------
 
 In the current version, each of the OpenCV CUDA algorithms can use only a single GPU. So, to utilize multiple GPUs, you have to manually distribute the work between GPUs.
-Switching active devie can be done using :ocv:func:`cuda::setDevice()` function.  For more details please read Cuda C Programing Guide.
+Switching active devie can be done using :ocv:func:`cuda::setDevice()` function.  For more details please read Cuda C Programming Guide.
 
 While developing algorithms for multiple GPUs, note a data passing overhead. For primitive functions and small images, it can be significant, which may eliminate all the advantages of having multiple GPUs. But for high-level algorithms, consider using multi-GPU acceleration. For example, the Stereo Block Matching algorithm has been successfully parallelized using the following algorithm: