Thermal video analysis for fire detection using shape regularity and intensity saturation features

  • Authors:

  • Mario I. Chacon-Murguia;Francisco J. Perez-Vargas

  • Affiliations:

  • Visual Perception Applications on Robotic Lab, Chihuahua Institute of Technology;Visual Perception Applications on Robotic Lab, Chihuahua Institute of Technology

  • Venue:
  • MCPR'11 Proceedings of the Third Mexican conference on Pattern recognition
  • Year:
  • 2011

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Abstract

This paper presents a method to detect fire regions in thermal videos that can be used for both outdoor and indoor environments. The proposed method works with static and moving cameras. The detection is achieved through a linear weighted classifier which is based on two features. The features are extracted from candidate regions by the following process; contrast enhance by the Local Intensities Operation and candidate region selection by thermal blob analysis. The features computed from these candidate regions are; region shape regularity, determined by Wavelet decomposition analysis and region intensity saturation. The method was tested with several thermal videos showing a performance of 4.99% of false positives in non-fire videos and 75.06% of correct detection with 7.27% of false positives in fire regions. Findings indicate an acceptable performance compared with other methods because this method unlike other works with moving camera videos.