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On approach to vision based fire detection based on type-2 fuzzy clustering

机译:基于型模糊聚类的基于视觉的火灾探测的方法

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During the last ten years computer vision techniques have shown a great potential in solving the problem of automatic fire detection. Vision-based fire detection offers many advantages over the conventional methods that use smoke and heat detectors. This paper presents a novel approach for fire detection by modeling the structure of spatial of fire, this structure is considered in terms of the color intensity of fire pixels. Furthers the type-2 fuzzy clustering technique is applied to separate fire-color pixels into some clusters, then these clusters are used to model structure of fire. Experimental results show that our method is capable of detecting fire in early state of fire and weak light-intensity environment; and this method uses only information on a single image so it can be integrated into the surveillance system that used dynamic camera.
机译:在过去的十年中,计算机视觉技术在解决自动火灾探测问题方面表现出很大的潜力。基于视觉的火灾检测提供了与使用烟雾和热量探测器的传统方法的许多优点。本文提出了一种新颖的火灾检测方法,通过建模火灾结构的结构,在火像素的颜色强度方面考虑这种结构。 Futthers Type-2模糊聚类技术应用于将火颜色像素分离成一些簇,然后这些簇用于模拟火灾结构。实验结果表明,我们的方法能够在初期火灾和弱光强环境下检测火灾。此方法仅在单个图像上使用信息,因此可以集成到使用动态摄像机的监控系统中。

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