
OpenCV stands for Open Source Computer Vision Library. It is a library of programming functions. This library was developed by Intel and is now supported by Willow Garage. It is free for use under the open source BSD license. The library is cross-platform. It focuses mainly on real-time image processing.
The library is written in C and C++ and runs under Linux, Windows and Mac OS X. There is active development on interfaces for Python, Ruby, Matlab, and other languages. OpenCV was designed for computational efficiency and with a strong focus on real time applications. OpenCV is written in optimized C and can take advantage of multi-core processors.
The OpenCV library contains over 500 functions that span many areas in vision, including factory medical imaging, security, user interface, camera calibration, stereo vision, and robotics. Because computer vision and machine learning often go hand-in- hand, OpenCV also contains a full, general-purpose Machine Learning Library (MLL). This sub-library is focused on statistical pattern recognition and clustering.
In the future posts, I will share my experience of using OpenCV, both on Windows and Linux platforms.
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