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BDTI Releases Quick-Start OpenCV Kit for Computer Vision Application Developers



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April 27, 2012 —  (Page 1 of 2)
Berkeley Design Technology, Inc., the technology industry's trusted source of analysis, advice, and engineering for embedded processing technology and applications, has released a free quick-start kit for engineers who want to start developing computer vision applications using OpenCV.  OpenCV is a free open source library of computer vision algorithm building block software components that is popular with engineers who are learning about computer vision and prototyping new algorithms and applications.  However, installing and configuring a development environment with OpenCV can be difficult for new users.  BDTI has solved this problem by offering a complete, pre-built OpenCV development environment in the form of a virtual machine image that can be downloaded and installed quickly and easily.  The BDTI Quick-Start OpenCV Kit is available free of charge to all.

The BDTI Quick-Start OpenCV Kit includes Ubuntu Linux, an Eclipse integrated development environment, GNU GCC tools, and OpenCV—all pre-installed and ready to run within a single virtual machine image that can be executed using the free VMware Player for PCs or using VMware Fusion for Macs.  In addition, BDTI has provided interactive, real-time example applications illustrating computer vision functions such as face detection and object tracking.

Originally developed by Intel Corporation, OpenCV is a software component library for computer vision algorithm and application development, first publicly released in 2000.  A powerful tool for prototyping vision algorithms, the OpenCV library includes over 2,500 functions and contains dozens of vision application examples.  It has been downloaded over 3.5 million times and has been used in a wide variety of applications, from collision avoidance to advanced robotics.

With the emergence of increasingly capable low-cost processors and image sensors, it is now becoming practical to incorporate computer vision capabilities into a wide range of embedded systems, enabling system to analyze their environment via image and video inputs.  Products like Microsoft's Kinect game controller and Mobileye's driver assistance systems are raising awareness of the incredible potential of embedded vision technology.  "Embedded vision technology is already having a huge impact on markets from factory automation to gaming, and from security to automotive safety," said Jon Cropley, principal analyst with market research firm IMS Research.  "As the enabling technologies for embedded vision become more capable and cost-effective, we expect embedded vision to proliferate into numerous other markets, including mobile devices, digital signs, medical equipment, and even toys."  As a result, many embedded system designers and mobile app developers are beginning to think about implementing embedded vision capabilities. For system designers and app developers, OpenCV can enable rapid experimentation and prototyping of new vision algorithms.




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