How to use ArUco marker with the openCV support package of MATLAB and the Computer Vision System Toolbox. [R2017b]

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MathWorks Support Team 2017-11-24

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https://ww2.mathworks.cn/matlabcentral/answers/372403-how-to-use-aruco-marker-with-the-opencv-support-package-of-matlab-and-the-computer-vision-system-too

回答： MathWorks Support Team 2017-12-11

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Is there a MATLAB Toolbox which supports the usage ArUco markers, which are part of OpenCV?

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Answer 1

MathWorks Support Team 2017-11-24

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/372403-how-to-use-aruco-marker-with-the-opencv-support-package-of-matlab-and-the-computer-vision-system-too#answer_295786

getaruco.cpp

There is no toolbox that can do this in MATLAB directly. But it is possible to get this functionality through OpenCV interface support package: https://www.mathworks.com/discovery/matlab-opencv.html Generally, the Computer Vision System Toolbox OpenCV Interface allows it to bring existing OpenCV files and projects into MATLAB using the MEX Interface.

For OpenCV 3 and above, the ArUco modules are part of the opencv_contrib _repository: https://github.com/opencv/opencv_contrib/tree/master/modules/aruco. Any module located in _opencv_contrib is not part of the core OpenCV library, and is therefore not build, linked or shipped with the OpenCV interface.

It is however possible, to build OpenCV with the _opencv_contrib _modules outside of MATLAB and its installation, and link against it while creating a MEX file. This procedure gives access to the functions of the _opencv_contrib _module of interest. The general steps are as follows:

OpenCV

download the source code of OpenCV 3.1 from here: <https://github.com/opencv/opencv/tree/3.1.0>
download the opencv_contrib repository from here: <https://github.com/opencv/opencv_contrib/tree/3.1.0>
Install openCV on your machine following the instructions here: <https://github.com/opencv/opencv_contrib/blob/master/README.md>
Note down where the libraries are built, and where the header files are copied.

MATLAB Computer Vision System Toolbox

install the Computer Vision System Toolbox, e.g. from MATLAB Desktop -> AddOns dropdown -> GetAddons (you can check if this toolbox is covered by your license typing ver in the Command Window)
install the OpenCV Interface support package following the instructions here: <https://www.mathworks.com/help/vision/ug/opencv-interface.html#buxwnlt>
(optional) video on “Using OpenCV with MATLAB (<http://youtu.be/BasC2jkgyaM>)”

ArUco

Use the attached getaruco.cpp file as an example, and run the following in the MATLAB Command Window:

>> mexOpenCV getaruco.cpp -L~/opencv310/lib/ -lopencv_aruco.3.1.0 -I/usr/local/include

It is important to replace the paths according to your OpenCV installation. Flag explanation

-L looks in directory for library files

-l links with a library file

-I adds include directory of header files

This should generate a MEX file called getaruco.mex* (* replaced by the OS identifier). Now you can use getaruco() like any other MATLAB function. In the provided example, to create a 1000-by-1000 uint8 image, with a markerId of 12, and border bits size 1, use

>> im = getaruco(1000, 12, 1);

You can then access any class from the ArUco module, by changing the mexFunction() in the getaruco.cpp file. It is suggested to create getArucoFunctionOne.cpp, getArucoFunctionTwo.cpp,etc. for different ArUco functions.