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Wavelet based smoke detection method with RGB Contrast-image and shape constrain

  • Jiaqiu Chen
  • , Yaowei Wang*
  • , Yonghong Tian
  • , Tiejun Huang
  • *Corresponding author for this work
  • Beijing Institute of Technology
  • Peking University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Smoke detection in video surveillance is very important for early fire detection. A general viewpoint assumes that smoke is a low frequency signal which may smoothen the background. However, some pure-color objects also have this characteristic, and smoke also produces high frequency signal because the rich edge information of its contour. In order to solve these problems, an improved smoke detection method with RGB Contrast-image and shape constrain is proposed. In this method, wavelet transformation is implemented based on the RGB Contrast-image to distinguish smoke from other low frequency signals, and the existence of smoke is determined by analyzing the combination of the shape and the energy change of the region. Experimental results show our method outperforms the conventional methods remarkably.

Original languageEnglish
Title of host publicationIEEE VCIP 2013 - 2013 IEEE International Conference on Visual Communications and Image Processing
DOIs
StatePublished - 2013
Externally publishedYes
Event2013 IEEE International Conference on Visual Communications and Image Processing, IEEE VCIP 2013 - Kuching, Sarawak, Malaysia
Duration: 17 Nov 201320 Nov 2013

Publication series

NameIEEE VCIP 2013 - 2013 IEEE International Conference on Visual Communications and Image Processing

Conference

Conference2013 IEEE International Conference on Visual Communications and Image Processing, IEEE VCIP 2013
Country/TerritoryMalaysia
CityKuching, Sarawak
Period17/11/1320/11/13

Keywords

  • RGB Contrast-image
  • Smoke detection
  • shape constrain
  • wavelet transform

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