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基于视频区域动态特征的林火烟雾检测技术研究

刘长春 刘鹏举 季烨云

刘长春, 刘鹏举, 季烨云. 基于视频区域动态特征的林火烟雾检测技术研究[J]. 北京林业大学学报, 2021, 43(1): 10-19. doi: 10.12171/j.1000-1522.20200049
引用本文: 刘长春, 刘鹏举, 季烨云. 基于视频区域动态特征的林火烟雾检测技术研究[J]. 北京林业大学学报, 2021, 43(1): 10-19. doi: 10.12171/j.1000-1522.20200049
Liu Changchun, Liu Pengju, Ji Yeyun. Research on forest fire smoke detection technology based on video region dynamic features[J]. Journal of Beijing Forestry University, 2021, 43(1): 10-19. doi: 10.12171/j.1000-1522.20200049
Citation: Liu Changchun, Liu Pengju, Ji Yeyun. Research on forest fire smoke detection technology based on video region dynamic features[J]. Journal of Beijing Forestry University, 2021, 43(1): 10-19. doi: 10.12171/j.1000-1522.20200049

基于视频区域动态特征的林火烟雾检测技术研究

doi: 10.12171/j.1000-1522.20200049
基金项目: 中国林业科学研究院基本科研业务费专项(CAFYBB2017ZC001),“948”国家林业局引进项目(2014-4-01)
详细信息
    作者简介:

    刘长春。主要研究方向:地理信息系统技术与应用。Email:lcc175@126.com 地址:100091 北京市海淀区香山路东小府1号中国林业科学研究院资源信息研究所

    责任作者:

    刘鹏举,博士,副研究员。主要研究方向:林业GIS应用与开发。Email:liupeng@caf.ac.cn 地址:同上

  • 中图分类号: S762.3+2

Research on forest fire smoke detection technology based on video region dynamic features

  • 摘要:   目的  视频监控越来越多地应用到森林火灾烟雾的早期检测中。现有的视频林火烟雾检测方法大多是基于像素提取烟雾特征进行分析检测,烟雾发生早期或烟雾距离摄像头较远时,在视频图像上烟雾仅呈现较小区域,且烟雾的扩散具有无规则性,背景环境复杂多变,导致基于像素的特征不明显,因此使基于像素的烟雾自动化检测难度增大。本文根据可见光视频图像处理原理,提出一种基于局部区域图像动态特征的林火视频烟雾检测方法,以提高林火视频烟雾检测准确度和灵敏度。  方法  以视频图像为研究对象,每秒取一帧生成图像序列,对图像序列进行多层次不同尺度分区;利用图像信噪比原理,计算分区后的连续图像序列的信噪比;根据背景图像信噪比得到自适应阈值,确定待检测图像序列发生亮度变化的图像块,即为疑似烟雾块;提取疑似烟雾块的LBP纹理特征,采用支持向量机区分出烟雾区域。  结果  利用HSV颜色空间的亮度分量,可以有效提取烟雾区域。选择有林火烟雾的视频,对提出的烟雾变化检测方法进行验证,分析结果表明该方法能确定烟雾发生所在的图像块,且能排除部分非烟雾干扰因素。  结论  本文提出了基于局部区域亮度特征和LBP纹理特征的视频林火烟雾检测技术,能准确定位烟雾发生区域,排除部分干扰因素,检测识别率平均达到92%以上,有助于实时林火烟雾自动检测,提高林火烟雾检测率,具有很强的实用性。

     

  • 图  1  分块后编码

    Figure  1.  Block encoding

    图  2  算法流程图

    Figure  2.  Algorithm flowchart

    图  3  Video4烟雾发生区域连续图像

    Figure  3.  Continuous image of smoke occurrence area in video4

    图  4  烟雾HSV颜色通道SNR变化趋势

    m表示参考帧取背景帧;n表示参考帧取前一帧。m indicates the reference frame taking the background frame; n indicates the reference frame taking the previous frame.

    Figure  4.  SNR changing trend of smoke HSV color channel

    图  5  SNR变化趋势

    SNRbg表示前一时间窗口内SNR的值。SNRbg indicates the value of SNR in the previous time window.

    Figure  5.  Changing trend of SNR

    图  6  非烟雾SNRm和SNRn变化趋势

    Figure  6.  Changing trend of non-smoke SNRm and SNRn

    图  7  不同分块方法得到SNR变化趋势

    Figure  7.  Changing trend of SNR by diffirent block methods

    图  8  检测结果

    Figure  8.  Detection results

    表  1  视频相关信息

    Table  1.   Video related information

    编号
    No.
    类别
    Classification
    视频名称
    Video name
    视频场景描述
    Video scene description
    帧速率/(帧·s−1)
    Frame rate/
    (frame·s−1)
    截取后总帧数
    Total number of frames after clip
    视频1 Video1 烟雾
    Smoke
    Pelco_Colakli 远距离,有风,烟雾扩散缓慢
    Long distance, windy, smoke spread slowly
    7 122
    视频2 Video2 烟雾
    Smoke
    20070817 Aksehir_Duman_Test5_
    en_Iyisi_near_487_frame
    远距离,有风,烟雾扩散缓慢
    Long distance, windy, smoke spread slowly
    7 484
    视频3 Video3 烟雾
    Smoke
    Smoke_Manavgat_Raw 远距离,烟雾较浓,扩散缓慢
    Long distance, thick smoke, slow diffusion
    25 242
    视频4 Video4 烟雾
    Smoke
    20090409 ManavgatTEst 远距离,有风,有车辆驶过,烟雾扩散缓慢
    Long distance, windy, vehicles passing by, smoke spread slowly
    9 180
    视频5 Video5 烟雾
    Smoke
    森林保护站拍摄视频1
    Video1 taken at the forest protection station
    近距离,有烟雾,卡车施工作业
    Close distance, smoke, truck construction operation
    25 238
    视频6 Video6 非烟雾
    Non-smoke
    森林保护站拍摄视频2
    Video2 taken at the forest protection station
    近距离,有云
    Close distance, cloudy
    30 220
    视频7 Video7 非烟雾
    Non-smoke
    森林保护站拍摄视频3
    Video3 taken at the forest protection station
    近距离,有行人经过
    Close distance, pedestrians passing by
    24 192
    视频8 Video8 非烟雾
    Non-smoke
    森林保护站拍摄视频4
    Video4 taken at the forest protection station
    近距离,有车辆驶过
    Close distance, vehicles passing by
    25 168
    下载: 导出CSV

    表  2  2 × 2分块方式

    Table  2.   2 × 2 block pattern

    编码 No.块0 Block 0块1 Block 1块2 Block 2块3 Block 3
    待检测区域信噪比的方差SNRvar SNRvar of the area to be detected5.477 50.041 30.054 20.053 1
    下载: 导出CSV

    表  4  8 × 8分块方式

    Table  4.   8 × 8 block pattern

    编码 No.块030 Block 030块031 Block 031块032 Block 032块033 Block 033
    待检测区域信噪比的方差SNRvar SNRvar of the area to be detected21.453 716.541 425.686 140.761 4
    下载: 导出CSV

    表  3  4 × 4分块方式

    Table  3.   4 × 4 block pattern

    编码 No.块00 Block 00块01 Block 01块02 Block 02块03 Block 03
    待检测区域信噪比的方差SNRvar SNRvar of the area to be detected0.083 51.738 10.677 114.888 5
    下载: 导出CSV

    表  5  测试结果

    Table  5.   Test results %

    烟雾视频数据 Smoke video data精确率 Precision (P)F1
    视频1 Video19095
    视频2 Video29396
    视频3 Video39095
    视频4 Video49598
    视频5 Video59396
    注:F1为精确率和召回率的调和平均数。Note: F1 is harmonic mean of precision and recall.
    下载: 导出CSV
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  • 收稿日期:  2020-02-23
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