Recognition Methods In Image Processing
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Image recognition is the process of identifying and detecting an object or a feature in a digital image or video.
This concept is used in many applications like systems for factory automation, toll booth monitoring, and security surveillance.
Typical image recognition algorithms include:
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Optical character recognition
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Pattern and gradient matching
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Face recognition
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License plate matching
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Scene change detection
OpenCV
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OpenCV is released under a BSD license and hence it’s free for both academic and commercial use. 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 9 million. Usage ranges from interactive art, to mines inspection, stitching maps on the web or through advanced robotics.
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Emgu CV
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Emgu CV is a cross platform .Net wrapper to the OpenCV image processing library. Allowing OpenCV functions to be called from .NET compatible languages such as C#, VB, VC++, IronPython etc. The wrapper can be compiled by Visual Studio, Xamarin Studio and Unity, it can run on Windows, Linux, Mac OS X, iOS, Android and Windows Phone.
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http://www.emgu.com/wiki/index.php/Main_Page
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