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      • Faculty of Engineering
      • Department of Electrical and Electronics Engineering
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      Contour based smoke detection in video using wavelets

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      Author
      Töreyin, B. Uğur
      Dedeoğlu, Yiğithan
      Çetin, A. Enis
      Date
      2006-09
      Source Title
      14th European Signal Processing Conference, 2006
      Publisher
      IEEE
      Language
      English
      Type
      Conference Paper
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      Abstract
      This paper proposes a novel method to detect smoke in video. It is assumed the camera monitoring the scene is stationary. The smoke is semi-transparent at the early stages of a fire. Therefore edges present in image frames start loosing their sharpness and this leads to a decrease in the high frequency content of the image. The background of the scene is estimated and decrease of high frequency energy of the scene is monitored using the spatial wavelet transforms of the current and the background images. Edges of the scene produce local extrema in the wavelet domain and a decrease in the energy content of these edges is an important indicator of smoke in the viewing range of the camera. Moreover, scene becomes grayish when there is smoke and this leads to a decrease in chrominance values of pixels. Periodic behavior in smoke boundaries is also analyzed using a Hidden Markov model (HMM) mimicking the temporal behavior of the smoke. In addition, boundary of smoke regions are represented in wavelet domain and high frequency nature of the boundaries of smoke regions is also used as a clue to model the smoke flicker. All these clues are combined to reach a final decision.
      Keywords
      Background image
      Energy content
      Final decision
      High frequency
      Image frames
      Local extremum
      Periodic behavior
      Semi-transparent
      Smoke detection
      Temporal behavior
      Wavelet domain
      Cameras
      Hidden Markov models
      Signal processing
      Smoke
      Permalink
      http://hdl.handle.net/11693/27137
      Published Version (Please cite this version)
      https://ieeexplore.ieee.org/document/7071763
      Collections
      • Department of Computer Engineering 1368
      • Department of Electrical and Electronics Engineering 3524
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