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Short introduction to OpenCV

OpenCV presentation for thesis
by

Przemysław Spodymek

on 16 December 2010

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Transcript of Short introduction to OpenCV

Short introduction to OpenCV OpenCV (Open Source Computer Vision) is a library of programming functions for real time computer vision. The library has >500 optimized algorithms.
It is used around the world.
Has >2M downloads and >40K people in the user group. Uses range from interactive art, to mine inspection, stitching maps on the web on through advanced robotics. OpenCV is released under a BSD license, it is free for both academic and commercial use. What is OpenCV? OpenCV's application areas include:
2D and 3D feature toolkits
Egomotion estimation
Facial recognition system
Gesture recognition
Human-Computer Interface (HCI)
Mobile robotics
Motion understanding
Object Identification
Segmentation and Recognition
Stereopsis Stereo vision: depth perception from 2 cameras
Structure from motion (SFM)
Motion tracking Written in C = portability

Wrappers for languages:
C#
Python
Ruby

Since version 2.0 includes C as well as a new C++ interface

New developments and algorithms in C++ interface = wrappers are lacking some of the OpenCV 2.0 features. Questions? Thank You! OS Support

OpenCV runs under:

FreeBSD
Linux (in conjugation of v4l)
Mac OS
Windows.

Official releases on sourceforge! Sum-up:

Open source computer vision library in C/C++.
Optimized and intended for real-time applications.
OS/hardware/window-manager independent.
Generic image/video loading, saving, and acquisition.
Both low and high level API. Features:

Image data manipulation (allocation, release, copying, setting, conversion).
Image and video I/O (file and camera based input, image/video file output).
Basic image processing (filtering, edge detection, corner detection, sampling and interpolation, color conversion, morphological operations, histograms, image pyramids). More features:

Structural analysis (connected components, contour processing, distance transform, various moments, template matching, Hough transform, polygonal approximation, line fitting, ellipse fitting, Delaunay triangulation).
Camera calibration (finding and tracking calibration patterns, calibration, fundamental matrix estimation, homography estimation, stereo correspondence).
Motion analysis (optical flow, motion segmentation, tracking). detailed Guide: http://opencv.willowgarage.com/wiki/InstallGuide Useful links:

http://sourceforge.net/projects/opencvlibrary/
http://www.cs.iit.edu/~agam/cs512/lect-notes/opencv-intro/opencv-intro.html
http://www.comp.leeds.ac.uk/vision/opencv/ How to install?

sudo apt-get install build-essential cmake

sudo apt-get install libgtk2.0-dev libavcodec-dev libavformat-dev libjpeg62-dev libtiff4-dev
sudo apt-get install libdc1394-22-dev libjasper-dev libgstreamer0.10-dev libgstreamermm-0.10-dev
sudo apt-get install libswscale-dev libv4l-dev libxine-dev libunicap-dev

cmake -D BUILD_EXAMPLES=ON -D CMAKE_INSTALL_PREFIX=/opt ~/OpenCV-2.1.0
make
sudo make install


sudo vi /etc/bash.bashrc and add the lines:
PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/opt/lib/pkgconfig
export PKG_CONFIG_PATH Main advantages:

Easy I/O operations
Ready-to-use filters
Easy display A bit of programming OpenCV examples use areas general tech info
Full transcript