OpenCV
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Latest revision as of 13:17, 23 August 2011
Contents |
- Web site: http://sourceforge.net/projects/opencvlibrary/
- Described version: 2.3.0
- Licensing: BSD license
- User documentation: http://opencv.willowgarage.com/wiki/OpenCVBooks http://opencv.willowgarage.com/documentation/index.html
- Download: http://sourceforge.net/projects/opencvlibrary/files/opencv-win/2.3/OpenCV-2.3.0rc-win-src.zip/download
- Source code: http://sourceforge.net/projects/opencvlibrary/files/opencv-unix/2.3/ https://sourceforge.net/projects/opencvlibrary/files/opencv-win/2.3/
Authors/Maintainers
- OpenCV Developers & Support: http://opencv.willowgarage.com/wiki/FullOpenCVWiki#Welcome.2BAC8-People.People http://sourceforge.net/projects/opencvlibrary/support http://tech.groups.yahoo.com/group/OpenCV/
Summary
Computer vision is everywhere-in security systems, manufacturing inspection systems, medical image analysis, Unmanned Aerial Vehicles, and more. It stitches Google maps and Google Earth together, checks the pixels on LCD screens, and makes sure the stitches in your shirt are sewn properly. OpenCV provides an easy-to-use computer vision framework and a comprehensive library with more than 500 functions that can run vision code in real time. Thus OpenCV (Open Source Computer Vision) is a library of programming functions for real time computer vision. OpenCV is written in C/C++ and Python and more recently supports GPUs. More specifically, the OpenCV GPU module is a set of classes and functions that utilize GPU computational capabilities. It is implemented using NVidia CUDA Runtime API, so only that vendor GPUs are supported. It includes utility functions, low level vision primitives as well as high level algorithms. The module is being developed as power infrastructure for fast vision algorithms building on GPU with some high level state of the art functionality. The CPU version of the library is employs a TBB parallelization strategy.
Features
Architectural/Functional Overview
Usage Overview
Dependacies
HP-SEE Applications
- Within the HP-SEE virtual research communities, the OpenCV library is used by the UPB team in the development of the EagleEye project, implementing Feature Extraction from Satellite Images Using Hybrid Computing Architectures – CPU-GPU. Also we can envisage a joint usage of OpenCV features with the Computer Science Department from the West University of Timisoara, and the Romanian Institute for Space Sciences for satellite image processing and manipulation.
Resource Centers
- NCIT-Cluster, RO
Usage by Other Projects and Communities
Recommendations for Configuration and Usage
http://opencv.willowgarage.com/wiki/FullOpenCVWiki#Welcome.2BAC8-Introduction.Tutorials http://opencv.willowgarage.com/wiki/FullOpenCVWiki#Welcome.2BAC8-OS.OSSpecificStuff