Using OpenCV with MATLAB
Using the OpenCV interface support package, you can integrate the OpenCV computer vision library with MATLAB® to perform algorithm development, data analysis, and numerical computation in MATLAB.
By integrating OpenCV with MATLAB, you can:
- Use and explore current research algorithms, whether they are implemented in MATLAB or OpenCV
- Use OpenCV algorithms with the convenience of the data access, image acquisition, and visualization capabilities in MATLAB
- Use MATLAB to explore, analyze, and debug designs that incorporate OpenCV algorithms
The OpenCV interface makes it easy to bring single functions and entire OpenCV based C++ projects into MATLAB using MEX. The OpenCV interface provides:
- Prebuilt OpenCV binaries that eliminate the need to compile and build OpenCV
- Build script to create OpenCV based MEX-files
- Data type conversions between MATLAB and OpenCV
- Examples to help get started with common workflows such as feature detection and extraction, image processing, and motion estimation
You can use Computer Vision System Toolbox™ to extend your work in MATLAB and OpenCV. The toolbox provides MATLAB algorithms for feature extraction, object detection and tracking, object recognition, and geometric camera calibration and 3D vision. It also supports rapid prototyping with features such as fixed-point arithmetic support and C-code generation.
Examples and How To
See also: Computer Vision System Toolbox, object detection, image recognition, object recognition, stereo vision, feature extraction, point cloud