Forest Fire Detection Based on Video Multi-Feature Fusion

被引:0
|
作者
Jie, Li [1 ]
Jiang, Xiao [1 ]
机构
[1] Beijing Forestry Univ, Sch Tecnol, Beijing, Peoples R China
关键词
forest fire detection; computer vision; fire detection; fire character; image process; image segmentation; sample;
D O I
10.1109/ICCSIT.2009.5234862
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the light of the problem of monitoring forest fire, the design strategy and practical implementation of establishing the monitor system based on digital image information are proposed. The system is based on the CCD configuration characteristics and color information to detect and locate fire. Manned lookout posts are commonly installed in the forests all around the world. In this project, a system capable of producing automatic fire alarms will be developed. It will be also possible to approximately determine the location of the fire and monitor the forest fires using wireless communications systems. The aim of the proposed system is to reduce the average fire detection rate and reduce the number of guards. This approach will reduce false alarms due to natural events. The experimental results show that it can effectively identify fire.
引用
收藏
页码:19 / 22
页数:4
相关论文
共 50 条
  • [41] Robust Lane Marking Detection Based on Multi-Feature Fusion
    Hernandez, Danilo Caceres
    Seo, Dongwook
    Jo, Kang-Hyun
    2016 9TH INTERNATIONAL CONFERENCE ON HUMAN SYSTEM INTERACTIONS (HSI), 2016, : 423 - 428
  • [42] Chinese Event Detection Based on Multi-Feature Fusion and BiLSTM
    Xu, Guixian
    Meng, Yueting
    Zhou, Xiaokai
    Yu, Ziheng
    Wu, Xu
    Zhang, Lijun
    IEEE ACCESS, 2019, 7 : 134992 - 135004
  • [43] Daytime water hazard detection based on multi-feature fusion
    Yao, Tuo-Zhong
    Xiang, Zhi-Yu
    Liu, Ji-Lin
    Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science), 2009, 43 (04): : 605 - 609
  • [44] The Underwater Target Detection Based on Multi-Feature Fusion Algorithm
    Xu Zhijing
    Cao Peipei
    2011 INTERNATIONAL CONFERENCE ON COMPUTERS, COMMUNICATIONS, CONTROL AND AUTOMATION (CCCA 2011), VOL II, 2010, : 460 - 463
  • [45] Android Malware Detection Based on Stacking and Multi-feature Fusion
    Zhaowei, Qin
    Nannan, Xie
    Gyamfi, Asiedu Collins
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2022, 13725 LNAI : 199 - 215
  • [46] Android Malware Detection Based on Stacking and Multi-feature Fusion
    Qin Zhaowei
    Xie Nannan
    Gyamfi, Asiedu Collins
    ADVANCED DATA MINING AND APPLICATIONS (ADMA 2022), PT I, 2022, 13725 : 199 - 215
  • [47] Algorithm of Moving Object Detection based on Multi-feature Fusion
    Cao, Jianrong
    Sun, Xuemei
    Zhao, Shusheng
    Wang, Yameng
    Gong, Shulan
    2017 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION (IEEE ICIA 2017), 2017, : 931 - 935
  • [48] A Surface Defect Detection Method Based on Multi-Feature Fusion
    Wu, Xiaojun
    Xiong, Huijiang
    Yu, Zhiyang
    Wen, Peizhi
    NINTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2017), 2017, 10420
  • [49] Detection of small infrared targets based on multi-feature fusion
    Lou, Yue
    Wang, Zhi-Cheng
    Li, Xin
    Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering, 2007, 36 (03): : 395 - 397
  • [50] Multi-feature fusion based outdoor water hazards detection
    Yao, Tuozhong
    Xiang, Zhiyu
    Liu, Jilin
    Xu, Dong
    2007 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, VOLS I-V, CONFERENCE PROCEEDINGS, 2007, : 652 - +