Technique for automatic forest fire surveillance using visible light image

被引:0
|
作者
Li, J [1 ]
Qi, QW [1 ]
Zou, XP [1 ]
Peng, H [1 ]
Jiang, LL [1 ]
Liang, YJ [1 ]
机构
[1] CAS, IGSNRR, Cartog Dept, Beijing, Peoples R China
关键词
forest fire surveillance; visible light image; spectrum feature; serial forest fire image;
D O I
暂无
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Fires are one of the major hazards to the forest. Governments of various countries spend an enormous amount of manpower and financial resources to prevent forest fires every year. Many research projects, which monitor and identify the forest fires, have been developed by using infrared remote sensing. In this paper image features of all kinds of forest fire and background surface objects on the visible light image are analyzed. On the base of spectrum feature of the fire and background surface objects in the visible spectrum, feasibility of the method using visible light image to recognize forest fire is discussed, and then a new method with visible light image is put forward to identify forest fires. Firstly, the features of serial forest fire frame are generalized, which establishes the theoretical foundation for further recognition. Secondly, suspicious fire area is found in single frame according to the difference of fire and background got from the first step. Thirdly, some erroneous judgments are eliminated in response to continuous serial frames. In the end Jinggang Mountain which locates in Jiangxi province of China is taken as an example. More than 30 segments of forest fire image flow, photographing in different climate and from various angles are used to identify forest fire. Conclusion can be drawn that the rate of recognition is 100%, and the rate of accuracy is 85%.
引用
收藏
页码:3135 / 3138
页数:4
相关论文
共 50 条
  • [41] A method of UAV visible light remote sensing image registration based on eigenvector technique
    Qian, Yuelei
    Shi, Hongbin
    Liu, Guangchun
    RESULTS IN ENGINEERING, 2023, 20
  • [42] Inference of Replanting in Forest Fire Affected Land Using Data Mining Technique
    Divya, T. L.
    Vijayalakshmi, M. N.
    COMPUTATIONAL INTELLIGENCE IN DATA MINING, VOL 1, CIDM 2015, 2016, 410 : 121 - 129
  • [43] Image Processing Based Forest Fire Detection using YCbCr Colour Model
    Prema, C. Emmy
    Vinsley, S. S.
    2014 IEEE INTERNATIONAL CONFERENCE ON CIRCUIT, POWER AND COMPUTING TECHNOLOGIES (ICCPCT-2014), 2014, : 1229 - 1237
  • [44] A NEW TECHNIQUE FOR VISUALIZATION OF FOREST FIRE SMOKE PLUMES USING MODIS DATA
    Nagatani, Izumi
    Kudoh, Jun-ichi
    Kawano, Koichi
    2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 2380 - 2383
  • [45] Forest Fire Pattern Extraction and Rule Generation using Sliding Window Technique
    Ku-Mahamud, Ku Ruhana
    Yun, Khor Jia
    COMPUTING & INFORMATICS, 2009, : 182 - 187
  • [46] Forest fire hazard rating assessment in peat swamp forest using Landsat thematic mapper image
    Razali, Sheriza M.
    Nuruddin, A. Ainuddin
    Malek, Ismail A.
    Patah, Norizan A.
    JOURNAL OF APPLIED REMOTE SENSING, 2010, 4
  • [47] Automatic Forest Fire Detection and Monitoring Techniques: A Survey
    Chowdary, Vinay
    Gupta, Mukul Kumar
    INTELLIGENT COMMUNICATION, CONTROL AND DEVICES, ICICCD 2017, 2018, 624 : 1111 - 1117
  • [48] Automatic Methodology for Forest Fire Mapping with SuperDove Imagery
    Rodriguez-Esparragon, Dionisio
    Gamba, Paolo
    Marcello, Javier
    SENSORS, 2024, 24 (16)
  • [49] The Study of Forest Fire Color Image Segmentation
    Li Si
    Ren Hong-e
    ADVANCED MATERIALS AND COMPUTER SCIENCE, PTS 1-3, 2011, 474-476 : 2140 - 2145
  • [50] On an image segmentation method for forest fire metrology
    Rudz, Steve
    Sero-Guillaume, O.
    Chetehouna, K.
    Hafiane, A.
    Laurent, H.
    PROCEEDINGS OF THE 7TH INTERNATIONAL SYMPOSIUM ON IMAGE AND SIGNAL PROCESSING AND ANALYSIS (ISPA 2011), 2011, : 171 - 176