Abstract
This paper proposes an efficient early fire detection approach using multi-stage pattern recognition techniques, including background subtraction for movement-containing region detection, statistical rule-based color segmentation in YCbCr color space, a single-level spatial wavelet decomposition for observing flicker of fire, and a support vector machine to identify between fire of non-fire. This paper evaluates the proposed approach in terms of percentage of true positive and false negative. Experimental results indicate that average fire detection and false non-fire detection rates are 99.67 and 3.69 %, respectively.
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Acknowledgments
This work was supported by the Leading Industry Development for Economic Region (LeadER) grant funded the MOTIE (Ministry of Trade, Industry and Energy), Korea in 2013 (No. R0001220) and by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. NRF-2013R1A2A2A05004566).
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Shon, D., Kang, M., Seo, J., Kim, JM. (2014). Early Fire Detection Using Multi-Stage Pattern Recognition Techniques in Video Sequences. In: Park, J., Zomaya, A., Jeong, HY., Obaidat, M. (eds) Frontier and Innovation in Future Computing and Communications. Lecture Notes in Electrical Engineering, vol 301. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-8798-7_20
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DOI: https://doi.org/10.1007/978-94-017-8798-7_20
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