MATLAB and OpenCV

Using MATLAB with OpenCV

You can integrate the OpenCV computer vision library with MATLAB^®, using the MEX interface, to perform algorithm development, data analysis, and numerical computation in MATLAB.

By integrating MATLAB and OpenCV 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

You can extend your work in MATLAB and OpenCV with Computer Vision System Toolbox^™. The toolbox provides MATLAB algorithms for feature extraction, motion detection, object detection, object tracking, and stereo vision. It also supports rapid prototyping with features like fixed-point arithmetic support and C-code generation.

Examples and How To

• MATLAB and OpenCV (Community Examples)
• Computer Vision with MATLAB (Webinar)
• Image Processing with MATLAB (Webinar)
• Image and Video Processing Applications (Solution)
• Face Detection and Tracking (Example)
• Pattern Matching (Example)
• Stereo Vision (Example)

Software Reference

• Feature Detection, Extraction, and Matching (Documentation)
• Locating Image Features (Documentation)
• Motion Analysis and Tracking (Documentation)

See also: Steve on Image Processing, image and video processing, image recognition, Face recognition, Object detection, Object recognition