Fire Detection Using Both Infrared and Visual Images With Application to Unmanned Aerial Vehicle Forest Fire Surveillance

C. Yuan, Zhixiang Liu, Anim Hossain, Youmin Zhang
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引用次数: 2

Abstract

Forest fires are a universal problem that destroy a large amount of natural resources and creates environmental pollution. Forest firefighting is one of today’s most important events for natural and environmental resources protection and conservation. Unmanned aerial vehicle (UAV) with remote sensing system can offer a rapid, safe and low-cost approach for effective forest fire detection which have attracted researchers attention worldwide. In this paper, automatic detection of fire regions using both visual and infrared images is investigated. In order to improve the computational performance to satisfy the requirement of real-time processing, a reduced complexity fusion method is adopted in this research. Through testing the proposed approach on real video sequences, good detection performance is achieved and it is indicated that using multi-modal camera system to detect forest fire with application to firefighting UAV is very promising.
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基于红外和视觉图像的火灾探测及其在无人机森林火灾监视中的应用
森林火灾是一个全球性的问题,它破坏了大量的自然资源,造成了环境污染。森林消防是当今保护和节约自然环境资源的重要活动之一。具有遥感系统的无人机为森林火灾的有效探测提供了一种快速、安全、低成本的方法,引起了国内外研究者的广泛关注。本文研究了利用视觉和红外图像对火灾区域进行自动检测的方法。为了提高计算性能以满足实时处理的要求,本研究采用了一种降低复杂度的融合方法。通过对真实视频序列的测试,该方法取得了良好的检测性能,表明将多模态摄像机系统用于森林火灾检测并应用于消防无人机是很有前景的。
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