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Development of Intelligent Surveillance System (ISS) in Region of Interest(ROI) using Kalman filter and Camshift on Raspberry pi 2

机译:使用Kalman滤波器和Camshift在Raspberry pi 2上开发感兴趣区域(ROI)的智能监视系统(ISS)

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摘要

Due to the improvement of the picture quality of closed-circuit television (CCTV), the demand for CCTV has increased rapidly and its market size has also increased. The current system structure of CCTV transfers compressed images without analysis received from CCTV to a control center. The compressed images are suitable for the evidence required for a criminal arrest, but they cannot prevent crime in real time, which has been considered a limitation. Thus, the present paper proposes a system implementation that can prevent crimes by applying a situation awareness system at the back end of the CCTV cameras for image acquisition to prevent crimes efficiently. In the system implemented in the present paper, the region of interest (ROI) is set virtually within the image data when a barrier, such as fence, cannot be installed in actual sites and unauthorized intruders are tracked constantly through data analysis and recognized in the ROI via the developed algorithm. Additionally, a searchlight or alarm sound is activated to prevent crime in real time and the urgent information is transferred to the control center. The system was implemented in the Raspberry Pi 2 board to be run in real time. The experiment results showed that the recognition success rate was 85% or higher and the track accuracy was 90% or higher. By utilizing the system, crime prevention can be achieved by implementing a social safety network.
机译:由于闭路电视(CCTV)的图像质量的提高,对CCTV的需求迅速增加,并且其市场规模也增加了。闭路电视的当前系统结构将未经压缩的压缩图像从闭路电视传输到控制中心。压缩的图像适合用于刑事逮捕所需的证据,但是它们不能实时防止犯罪,这被认为是一种限制。因此,本文提出了一种系统实现,该系统实现可以通过在闭路电视摄像机后端应用态势感知系统进行图像采集来预防犯罪,从而有效地预防犯罪。在本文中实现的系统中,当障碍物(例如栅栏)无法安装在实际场所中并且通过数据分析不断跟踪未经授权的入侵者并将其识别时,在图像数据中虚拟地设置了感兴趣区域(ROI)。通过开发的算法获得投资回报。此外,探照灯或警报声会被激活以实时防止犯罪,并将紧急信息传送到控制中心。该系统已在Raspberry Pi 2板上实现,可以实时运行。实验结果表明,识别成功率为85%或更高,跟踪精度为90%或更高。通过使用该系统,可以通过实施社会安全网络来实现犯罪预防。

著录项

  • 来源
    《Pattern recognition》|2017年|104431B.1-104431B.8|共8页
  • 会议地点 Singapore(SG)
  • 作者

    Junghun Park; Kicheon Hong;

  • 作者单位

    Dept of Information and Telecommunications Engineering, University of Suwon Wau-ri, Bongdam-eup, Hwaseong-si, Gyeonggi-do, 445-743, Korea;

    Dept of Information and Telecommunications Engineering, University of Suwon Wau-ri, Bongdam-eup, Hwaseong-si, Gyeonggi-do, 445-743, Korea;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    situation awareness system; region of interest; Raspberry Pi 2; Kalman filter and Camshift;

    机译:态势感知系统;感兴趣的区域; Raspberry Pi 2;卡尔曼滤波器和Camshift;
  • 入库时间 2022-08-26 14:06:55

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