• DocumentCode
    3074833
  • Title

    UAV-based forest fire detection and tracking using image processing techniques

  • Author

    Chi Yuan ; Zhixiang Liu ; Youmin Zhang

  • Author_Institution
    Dept. of Mech. & Ind. Eng., Concordia Univ., Montreal, QC, Canada
  • fYear
    2015
  • fDate
    9-12 June 2015
  • Firstpage
    639
  • Lastpage
    643
  • Abstract
    In this paper, an unmanned aerial vehicle (UAV) based forest fire detection and tracking method is proposed. Firstly, a brief illustration of UAV-based forest fire detection and tracking system is presented. Then, a set of forest fire detection and tracking algorithms are developed including median filtering, color space conversion, Otsu threshold segmentation, morphological operations, and blob counter. The basic idea of the proposed method is to adopt the channel “a” in Lab color model to extract fire-pixels by making use of chromatic features of fire. Numerous experimental validations are carried out, and the experimental results show that the proposed methodology can effectively extract the fire pixels and track the fire zone.
  • Keywords
    autonomous aerial vehicles; fires; image colour analysis; image segmentation; median filters; object detection; object tracking; robot vision; UAV-based forest fire detection; UAV-based forest fire tracking; blob counter; chromatic features; color space conversion; fire zone; fire-pixels; image processing techniques; lab color model; median filtering; morphological operations; otsu threshold segmentation; unmanned aerial vehicle; Feature extraction; Fires; Image color analysis; Image segmentation; Morphological operations; Real-time systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Unmanned Aircraft Systems (ICUAS), 2015 International Conference on
  • Conference_Location
    Denver, CO
  • Print_ISBN
    978-1-4799-6009-5
  • Type

    conf

  • DOI
    10.1109/ICUAS.2015.7152345
  • Filename
    7152345