OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products. As OpenCV is based on BSD license, it allows individual researchers or organizations to use OpenCV libraries either in parts or in whole without forcing code to be open. But OpenCV expects users of these libraries will contribute back to make it more powerful.
History of OpenCV
OpenCV is an open-source computer vision library available from http://opencv.org. In 1999 Gary Bradski, working at Intel Corporation launched OpenCV with the hopes of accelerating computer vision and artificial intelligence by providing a solid infrastructure for everyone working in the field. The library is written in C and C++ and runs under Linux, Windows, and Mac OS X. Below image shows the timeline of OpenCV development.
OpenCV has C++, Python, Java, and MATLAB interfaces and supports Windows, Linux, Android, and Mac OS. OpenCV leans mostly towards real-time vision applications and takes advantage of MMX and SSE instructions when available. A full-featured CUDAand OpenCL interfaces are being actively developed right now. There are over 500 algorithms and about 10 times as many functions that compose or support those algorithms. OpenCV is written natively in C++ and has a templated interface that works seamlessly with STL containers.
Where is OpenCV used?
OpenCV is in active use in multiple domains which require analysis of images and videos. A few of the notable mentions are as follows.
Google Maps, Google Street View, Google Earth, Books
Academic and Industry Research
Safety monitoring
Security systems
Image retrieval
Structure from motion in movies
Machine Vision factory production inspection systems
Robotics
Automotive
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