首页> 外文会议>International Conference on Intelligent Computing(ICIC 2007); 20070821-24; Qingdao(CN) >Real-Time Fire Detection Using Camera Sequence Image in Tunnel Environment
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Real-Time Fire Detection Using Camera Sequence Image in Tunnel Environment

机译:在隧道环境中使用摄像机序列图像进行实时火灾探测

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摘要

In this paper, we proposed image processing technique for automatic real time fire and smoke detection in tunnel environment. To avoid the large scale of damage of fire occurred in the tunnel, it is necessary to have a system to minimize and to discover the incident as fast as possible. However it is impossible to keep the human observation of Closed-Circuit Television (CCTV) in tunnel for 24 hour. So if the fire and smoke detection system through image processing can warn fire state, it will be very convenient, and it can be possible to minimize damage even when people is not in front of monitor. The fire and smoke detection is different from the forest fire detection as there are elements such as car and tunnel lights and others that are different from the forest environment so that an indigenous algorithm has to be developed. The two algorithms proposed in this paper, are able to detect the exact position, at the earlier stage of incident. In addition, by comparing properties of each algorithm throughout experiment, we have proved the validity and efficiency of proposed algorithm.
机译:在本文中,我们提出了用于隧道环境中自动实时火灾和烟雾检测的图像处理技术。为了避免在隧道中发生大范围的火灾,必须有一个系统来尽可能地减少和发现事故。但是,不可能在隧道中将人类观察闭路电视(CCTV)保持24小时。因此,如果通过图像处理的火灾和烟雾检测系统可以警告火灾状态,则将非常方便,并且即使在人们不在显示器前的情况下,也可以将损坏降至最低。火灾和烟雾检测与森林火灾检测不同,因为汽车和隧道灯等元素与森林环境不同,因此必须开发一种本地算法。本文提出的两种算法能够在事件的早期阶段检测出精确的位置。此外,通过在整个实验过程中比较每种算法的属性,我们证明了所提算法的有效性和有效性。

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