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Fire Technology

, Volume 46, Issue 3, pp 651–663 | Cite as

Video Fire Smoke Detection Using Motion and Color Features

  • Yu Chunyu
  • Fang Jun
  • Wang Jinjun
  • Zhang Yongming
Article

Abstract

A novel video smoke detection method using both color and motion features is presented. The result of optical flow is assumed to be an approximation of motion field. Background estimation and color-based decision rule are used to determine candidate smoke regions. The Lucas Kanade optical flow algorithm is proposed to calculate the optical flow of candidate regions. And the motion features are calculated from the optical flow results and use to differentiate smoke from some other moving objects. Finally, a back-propagation neural network is used to classify the smoke features from non-fire smoke features. Experiments show that the algorithm is significant for improving the accuracy of video smoke detection and reducing false alarms.

Keywords

Video smoke detection Fire detection Motion features Optical flow Neural network 

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Yu Chunyu
    • 1
  • Fang Jun
    • 1
  • Wang Jinjun
    • 1
  • Zhang Yongming
    • 1
  1. 1.State Key Laboratory of Fire ScienceUSTCHefeiChina

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