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Fire detection using infrared images for UAV-based forest fire surveillance

机译:基于UV的森林火灾监测的红外图像火灾探测

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Unmanned aerial vehicle (UAV) based computer vision system, as a more and more promising option for forest fires surveillance and detection, is now widely employed. In this paper, an image processing method for the application to UAV is presented for the automatic detection of forest fires in infrared (IR) images. The presented algorithm makes use of brightness and motion clues along with image processing techniques based on histogram-based segmentation and optical flow approach for fire pixels detection. First, the histogram-based segmentation is used to extract the hot objects as fire candidate regions. Then, the optical flow method is adopted to calculate motion vectors of the candidate regions. The motion vectors are also further analyzed to distinguish fires from other fire analogues. Through performing morphological operations and blob counter method, a fire can be finally tracked in each IR image. Experimental results verified that the designed method can effectively extract and track fire pixels in IR video sequences.
机译:基于无人机的空中车辆(UAV)计算机视觉系统,作为森林火灾监测和检测的越来越有前途的选择,现在广泛采用。在本文中,介绍了应用于UAV的应用方法,用于红外(IR)图像中森林火灾的自动检测。该算法利用亮度和运动线索以及基于直方图的分割和光学流动方法的图像处理技术,用于火像素检测。首先,基于直方图的分割用于将热对象提取为火候选区域。然后,采用光学流量来计算候选地区的运动向量。还进一步分析运动载体以区分来自其他火焰类似物的火灾。通过执行形态操作和BLOB计数器方法,可以在每个IR图像中最终跟踪火灾。实验结果证实,设计的方法可以有效地提取和跟踪IR视频序列中的火像素。

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