• DocumentCode
    1967207
  • Title

    Large Space Fire Image Processing of Improving Canny Edge Detector Based on Adaptive Smoothing

  • Author

    Jiang, Qin ; Wang, Qiang

  • Author_Institution
    Coll. of Metrol. & Meas. Instrum., China Jiliang Univ., Hangzhou, China
  • fYear
    2010
  • fDate
    30-31 Jan. 2010
  • Firstpage
    264
  • Lastpage
    267
  • Abstract
    To avoid the large-scale damage caused by fire occurring in large space building, there are many studies about image-processing technique for automatic real-time flame detection. Adaptive Canny edge algorithm and flame geometric features are combined to inspect flame area of video data generated by an ordinary camera monitoring. Firstly, candidate fire regions are detected using modified Canny operator method which combines adaptive smoothing to detect moving fire regions. Fire regions generally have a higher luminance contrast than neighboring regions, a luminance map is made and used to remove non-fire pixels. The proposed selection criterion is effective in improving the performances of traditional Canny operator. Experimental results showed that the proposed approach was more robust to noise, and help to separate consecutive frames flame area.
  • Keywords
    building; edge detection; fires; flames; video cameras; Canny edge detector; adaptive Canny edge algorithm; adaptive smoothing; automatic real-time flame detection; camera monitoring; flame geometric features; large space building; large space fire image processing; modified Canny operator method; video data; Cameras; Detectors; Extraterrestrial measurements; Fires; Frequency; Image edge detection; Image processing; Image segmentation; Smoothing methods; Space technology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Computing & Communication, 2010 Intl Conf on and Information Technology & Ocean Engineering, 2010 Asia-Pacific Conf on (CICC-ITOE)
  • Conference_Location
    Macao
  • Print_ISBN
    978-1-4244-5634-5
  • Electronic_ISBN
    978-1-4244-5635-2
  • Type

    conf

  • DOI
    10.1109/CICC-ITOE.2010.73
  • Filename
    5439215