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Design and implementation of real time image inspection system

机译:实时图像检测系统的设计与实现

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With the rapid development of the embedded system, semiconductor technology and Image processing, the embedded Image processing has found widespread acceptance in mobile applications like video streaming, smart cameras, target tracking, vehicle navigation, smart traffic light systems and Biometrics. The implementation of image processing algorithms is computationally intensive and resource exhaustive. The system engineer has a mandate to optimize these algorithms so as to meet real time deadlines on an embedded processor. The designed system implements different real time image processing algorithms such as LPF, HPF, Threshoding, Template Matching on WINDOWS-XP and verified on WINDOWS 7 using Microsoft Visual Studio IDE VC++, further algorithms are implemented on Linux real time operating system(RTOS). The system uses the code optimization method to improve execution time for Viola Jones face detection algorithm. The design and implementation of real time image inspection system is based on the BeagleBoard-xM, a low cost ARM processor. This approach reduces size, efficiency, cost, time and power consumption etc. for Industrial control system based on real time image inspection system.
机译:随着嵌入式系统的快速发展,半导体技术和图像处理,嵌入式图像处理在视频流,智能摄像机,目标跟踪,车辆导航,智能交通灯系统和生物识别器等移动应用中发现了广泛的验收。图像处理算法的实现是计算密集和资源的详尽。系统工程师具有优化这些算法的任务,以便满足嵌入式处理器上的实时截止日期。设计系统实现了不同的实时图像处理算法,如LPF,HPF,阈值,模板匹配,在Windows-XP上验证,使用Microsoft Visual Studio IDE VC ++在Windows 7上验证,在Linux实时操作系统(RTOS)上实现了其他算法。该系统使用代码优化方法来改进Viola Jones面部检测算法的执行时间。实时图像检测系统的设计和实现基于BeagleBoard-XM,一个低成本的臂处理器。该方法降低了基于实时图像检测系统的工业控制系统的尺寸,效率,成本,时间和功耗等。

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