ANPR Day 8: Introduction to OpenCV Library

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With the viral spread of digital technology in today's world, it has also reached the shores of our country. The spark of digital revolution has been lighted by the advent of powerful and affordable computing devices, as well as internet. This has also created a ocean of videos and images everywhere. For anyone who wishes to develop simple or sophisticated imaging applications, OpenCV library is the tool to use.

OpenCV (Open Source Computer Vision) is an open source library containing more than 500 optimized algorithms for image and video analysis. Since its introduction in 1999, it has been largely adopted as the primary development tool by the community of researchers and developers in computer vision. OpenCV was originally developed at Intel by a team led by Gary Bradski as an initiative to advance research in vision and promote the development of rich, vision-based CPU-intensive applications.

It has C++, C, Python and Java interfaces and supports Windows, Linux, Mac OS, iOS and Android. OpenCV was designed for computational efficiency and with a strong focus on real-time applications. Written in optimized C/C++, the library can take advantage of multi-core processing. Enabled with OpenCL, it can take advantage of the hardware acceleration of the underlying heterogeneous compute platform. Adopted all around the world, OpenCV has more than 47 thousand people of user community and estimated number of downloads exceeding 7 million. Usage ranges from interactive art, to mines inspection, stitching maps on the web or through advanced robotics.

Sources:  http://en.wikipedia.org/wiki/OpenCV, http://opencv.org/, http://opencv.willowgarage.com/wiki/

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