Why use OpenCV

MINT green robotics project laboratory

OpenCV: An open source library for professional image processing

OpenCV ("Computer Vision") is a collection of algorithms and data structures for image processing, recognition and interpretation, to which the international academic and industrial image processing community is constantly adding new parts.

Many of the procedures included are state-of-the-art, others are obscure, and unfortunately most of them are only documented in an extremely spartan manner.

The "OpenCV" library for Processing

Greg Borenstein offers a wrapper ("packaging") for the "real" OpenCV library for processing under the same name as the original. This offers particularly easy installation and directly executable example programs.

In addition, the library offers an "opencv" class (the confusion never stops), in which the author bundles everything he thinks is useful into a large lump that is supposed to be easier to use than the chic, freely combinable modules of the original (the object-oriented programmer's stomach turns here ...). The original modules can still be used.


To install you just have to go to Processing in the menu Import Sketch / Library / Add Library select and the library "OpenCV" search.

If you want to use data from a camera, you also have to install the "Video" library. (works the same way).

Documentation and sources of information

Useful example: "LiveCamTest"

Next, maybe take a look at the example ‚ÄúContributedLibraries / OpenCV / LiveCamTest‚ÄĚ - there the built-in camera of your laptop is used to recognize and mark faces.

If you have nothing else in mind, you can usually use the code from the examples almost exactly.

Useful tutorials, unfortunately only for C ++

An overview of all functions implemented in the processing wrapper: JavaDoc

Indispensable for a deeper understanding: A look at the source code

Last modified: 2016/07/13 14:43 by