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首页> 外文期刊>International Journal of Information Acquisition >REAL-TIME FIRE AND SMOKE DETECTION USING CAMERA SEQUENCE IMAGE IN TUNNEL ENVIRONMENT
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REAL-TIME FIRE AND SMOKE DETECTION USING CAMERA SEQUENCE IMAGE IN TUNNEL ENVIRONMENT

机译:隧道环境中基于相机序列图像的实时火灾与烟雾检测

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摘要

In this paper, we proposed an image processing technique for automatic real time fire and smoke detection in tunnel environment. To avoid the large scale of damage of fire occurring in the tunnel, it is necessary to have a system to sense and minimize the incident as fast as possible. However it is impossible for human observation of Closed-Circuit Television (CCTV) in tunnel for 24 h. So if the fire and smoke detection system through image processing can warn a fire, it will be very convenient, and it can be possible to minimize damage even when no one is in front of the monitor. The fire and smoke detection is different from forest fire detection as there are elements such as car and tunnel lights and others that are different from the forest environment so 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,我们提出了一种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快地感应并最小化事故。然而,人类不可能在24小时内观察隧道中的闭路电视(CCTV)。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,则将非常方便,并且即使没有人在监视器前,也可以将损失降到最低。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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