A New Approach to Vision-Based Fire Detection Using Statistical Features and Bayes Classifier

  • Ha Dai Duong
  • Dao Thanh Tinh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7673)

Abstract

Computer vision - based fire detection has recently attracted a great deal of attention from the research community. In this paper, the authors propose and analyse a new approach for identifying fire in videos. In this approach, we propose a combined algorithm for detecting the fire in videos based on the changes of the statistical features in the fire regions between different frames. The statistical features consist of the average of the red, green and blue channel, the coarseness and the skewness of the red channel distribution. These features are evaluated, and then classified by Bayes classifier, and the final result is defined as fire-alarm rate for each frame. Experimental results demonstrate the effectiveness and robustness of the proposed method.

Keywords

Fire detection Pattern recognition Bayes classification 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Ha Dai Duong
    • 1
  • Dao Thanh Tinh
    • 1
  1. 1.Faculty of Information TechnologyLe Quy Don Technical UniversityCau GiayVietnam

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