4 January 2013 Efficient video-equipped fire detection approach for automatic fire alarm systems
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This paper proposes an efficient four-stage approach that automatically detects fire using video capabilities. In the first stage, an approximate median method is used to detect video frame regions involving motion. In the second stage, a fuzzy c-means-based clustering algorithm is employed to extract candidate regions of fire from all of the movement-containing regions. In the third stage, a gray level co-occurrence matrix is used to extract texture parameters by tracking red-colored objects in the candidate regions. These texture features are, subsequently, used as inputs of a back-propagation neural network to distinguish between fire and nonfire. Experimental results indicate that the proposed four-stage approach outperforms other fire detection algorithms in terms of consistently increasing the accuracy of fire detection in both indoor and outdoor test videos.
© 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)
Myeongsu Kang, Myeongsu Kang, Truong Xuan Tung, Truong Xuan Tung, Jong-Myon Kim, Jong-Myon Kim, } "Efficient video-equipped fire detection approach for automatic fire alarm systems," Optical Engineering 52(1), 017002 (4 January 2013). https://doi.org/10.1117/1.OE.52.1.017002 . Submission:


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