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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,半导体技术和图像处理技术的飞速发展,嵌入式图像处理技术已在视频流,智能相机,目标跟踪,车辆导航,智能交通灯系统和生物识别技术等移动应用中得到广泛认可。图像处理算法的实现需要大量的计算和资源。系统工程师有权优化这些算法,以便满足嵌入式处理器上的实时期限。设计的系统在WINDOWS-XP上实现了不同的实时图像处理算法,例如LPF,HPF,Throsododing,模板匹配,并使用Microsoft Visual Studio IDE VC ++在WINDOWS 7上进行了验证,进一步的算法在Linux实时操作系统(RTOS)上实现。系统使用代码优化方法来改善Viola Jones面部检测算法的执行时间。实时图像检查系统的设计与实现基于低成本ARM处理器BeagleBoard-xM。这种方法减少了基于实时图像检查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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