• DocumentCode
    588772
  • Title

    A Smoke Detection Algorithm Based on Discrete Wavelet Transform and Correlation Analysis

  • Author

    Wu Meng-Yu ; Han Ning ; Luo Qin-Juan

  • Author_Institution
    Sch. of Technol., Beijing Forestry Univ., Beijing, China
  • fYear
    2012
  • fDate
    2-4 Nov. 2012
  • Firstpage
    281
  • Lastpage
    284
  • Abstract
    A smoke detection algorithm based on Discrete Wavelet Transform and Correlation Analysis is presented to distinguish smoke and other smoke-like objects, especially cloud. Firstly, based on Gaussian mixture model, the target region of image is picked up. Secondly, we use Discrete Wavelet Transform to discriminate low frequency content and high frequency content of the images. At last, the high frequency information is analyzed by correlation. According to this algorithm, the motion region is smoke or not can be distinguished effectively and reliably. Experimental results show that the proposed method can improve the accuracy of smoke detection and reduce the false alarm.
  • Keywords
    Gaussian processes; correlation theory; discrete wavelet transforms; image motion analysis; object detection; smoke detectors; Gaussian mixture model; correlation analysis; discrete wavelet transform; frequency information analysis; image frequency content; image motion region; smoke detection algorithm; Correlation; Discrete wavelet transforms; Fires; Monitoring; Wavelet analysis; Discrete Wavelet Transform; cloud; correlation; forest fire smoke; target segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Information Networking and Security (MINES), 2012 Fourth International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4673-3093-0
  • Type

    conf

  • DOI
    10.1109/MINES.2012.46
  • Filename
    6405679