Automatic fire detection system using CCD camera and Bayesian network

Kwang-Ho Cheong; Byoung-Chul Ko; Jae-Yeal Nam

doi:10.1117/12.764822

26 February 2008 Automatic fire detection system using CCD camera and Bayesian network

Kwang-Ho Cheong, Byoung-Chul Ko, Jae-Yeal Nam

Proceedings Volume 6813, Image Processing: Machine Vision Applications; 68130S (2008) https://doi.org/10.1117/12.764822
Event: Electronic Imaging, 2008, San Jose, California, United States

Abstract

This paper proposes a new vision-based fire detection method for real-life application. Most previous vision-based methods using color information and temporal variations of pixels produce frequent false alarms due to the use of many heuristic features. Plus, there is usually a computation delay for accurate fire detection. Thus, to overcome these problems, candidate fire regions are first detected using a background model and color model of fire. Probabilistic models of fire are then generated based on the fact that fire pixel values in consecutive frames change constantly and these models are applied to a Bayesian Network. This paper uses a three-level Bayesian Network that contains intermediate nodes, and uses four probability density functions for evidence at each node. The probability density functions for each node are modeled using the skewness of the color red and three high frequency components obtained from a wavelet transform. The proposed system was successfully applied to various fire-detection tasks in real-world environments and effectively distinguished fire from fire-colored moving objects.

Citation Download Citation

Kwang-Ho Cheong, Byoung-Chul Ko, and Jae-Yeal Nam "Automatic fire detection system using CCD camera and Bayesian network", Proc. SPIE 6813, Image Processing: Machine Vision Applications, 68130S (26 February 2008); https://doi.org/10.1117/12.764822

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