OPENCV \ library

Processing and Java Library

OpenCV is an open source computer vision library originally developed by Intel. It is free for commercial and research use under a BSD license. The library is cross-platform, and runs on Mac OS X, Windows and Linux. It focuses mainly towards real-time image processing, as such, if it finds Intel's Integrated Performance Primitives on the system, it will use these commercial optimized routines to accelerate itself.

This implementation is not a complete port of OpenCV. Currently, this library supports :

real-time capture
video file import
basic image treatment (brightness, contrast, threshold, …)
object detection (face, body, …)
blob detection

Future versions will include more advanced functions such as motion analysis, object and color tracking, multiple OpenCV object instances …

For more information about OpenCV visit the Open Source Computer Vision Library Intel webpage, the OpenCV Library Wiki, and the OpenCV Reference Manual (pdf).

Installation instructions

Begin by downloading and installing the implementation of OpenCV appropriate to your platform:
- For Windows, download the OpenCV release version 1.0 (not the 1.1pre1) package and follow the instructions of the installer.
  notes: be sure to select the additional tasks 'Add <...>\OpenCV\bin to system PATH' during installation (or you need to add the rigth path by yourself later) and reboot your machine.
- For MacOS X, dowload the opencv-framework-1.1.dmg image and install the package by following instructions of the installer
- For Linux users, if your distribution doesn't propose packages in your favorite Package Manager tool, download the latest opencv-*.tar.gz archive and compile/install the source files as describe in the Linux install guide.
Download, unzip, and move the OpenCV Processing Library into your Processing libraries folder, or for Java users copy the content of the library folder in one of your Java Extensions folder.

DUE TO AN ERROR WHILE PACKAGING THE ZIP FILE, THIS VERSION UPDATED SHOULD SOLVE THE WINDOWS PROBLEM ABOUT DLL DEPENDENCIES AND OPENCV 1.0
Optionally, you can download these OpenCV Processing examples or, for pure Java users, these OpenCV Java samples.
Previous library version can be downloaded here

Documentation

See the What's New document for all new implementation or for some of the most important changes
Processing documentation … :) start with this page (also include in the OpenCV Processing Library zip archive)
For Java users, the Javadoc reference for this project (online only). For offline documentation dowload the OpenCV Java Library API

Credits

The OpenCV Processing Library is a project of the Atelier hypermédia at the École Supérieure d'Art d'Aix-en-Provence. It is maintained by Stéphane Cousot and Douglas Edric Stanley. Special thanks to the openframeworks community for support and the C++ Binary Quicksort method.

OpenCV
The main object for all computer vision processes.

To use OpenCV library in a PApplet directly in pure Java, start with this small integration sample
for more details about Processing see the home page


	import processing.core.*;
	import hypermedia.video.OpenCV;

	public class OpenCV_PApplet extends PApplet {

		OpenCV cv = null;  // OpenCV object

		// Initialise Objects
		public void setup() {
		    size( 640, 480 );              // set frame size
		    cv = new OpenCV( this );       // link OpenCV process to this PApplet
		    cv.capture( width, height );   // start video stream
		}

		// Display the input camera stream in frame
		public void draw() {
		    cv.read();
		    image( cv.image(), 0, 0 );
		}

		// Call the PApplet main method
		public static void main( String[] args ) {
		    PApplet.main( new String[]{"OpenCV_PApplet"} );
		} 
	}

OpenCV
ROI()
absDiff()
allocate()
blobs()
blur()
brightness()
capture()
cascade()
contrast()
convert()
copy()
detect()
flip()
image()
interpolation()
invert()
jump()
loadImage()
movie()
pixels()
read()
remember()
restore()
stop()
threshold()

Blob
A storage object containing a blob detected by OpenCV. Returned by blobs() method.

Blob