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AN ALGORITHM FOR SMOKE ROF DETECTION BASED ON SURVEILLANCE VIDEO

机译:基于监控视频的烟雾机器人检测算法

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摘要

In this paper, an algorithm for smoke region of focus (ROF) detection based on surveillance video is proposed in order to solve the problem of limited application in scenes range and imaging environment of the traditional smoke detection algorithm. The frog vision perception model is used in this algorithm. First the suspect regions are detected, and then the static and the dynamic features of the regions are chosen for the smoke ROF detection. Experimental results show that the algorithm is efficient and significant for improving the operational rate of the detection.
机译:为了解决传统烟雾探测算法在场景范围和成像环境中应用受限的问题,提出了一种基于监控视频的烟雾聚焦区域(ROF)检测算法。该算法使用青蛙视觉感知模型。首先检测可疑区域,然后选择区域的静态和动态特征进行烟雾ROF检测。实验结果表明,该算法有效提高了检测的操作率。

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  • 来源
    《Journal of Circuits, Systems, and Computers》 |2013年第3期|1350010.1-1350010.12|共12页
  • 作者单位

    Department of Electronic Science and Technology,College of Electronic Science and Engineering,National University of Defense Technology,Changsha, CO 410073, P. R. China;

    Department of Electronic Science and Technology,College of Electronic Science and Engineering,National University of Defense Technology,Changsha, CO 410073, P. R. China;

    Department of Electronic Science and Technology,College of Electronic Science and Engineering,National University of Defense Technology,Changsha, CO 410073, P. R. China;

    School of Electronic Engineering, Xidian University,Xi'an, CO 710071, P. R. China;

    Department of Electronic Science and Technology,College of Electronic Science and Engineering,National University of Defense Technology,Changsha, CO 410073, P. R. China;

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

    Surveillance video; smoke ROF; motion detection; static feature; dynamic feature.;

    机译:监控录像;烟雾ROF;运动检测;静态特征;动态功能。;

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