Early Flame Detection by Using Dynamic Accumulated Model

Abstract:

In order to solve the problem of early fire detection in the large space, a dynamic accumulated model is presented. The motion object is firstly obtained by using adaptive background subtraction. Three combined rules for flame detection are utilized. Dynamic accumulated model is implemented to compute the edge flicker of the motion object. Two features including circularity and area change are utilized to distinguished flame from other moving object. Experimental results indicate that the presented method has quick respond and can be used in outdoor environment.

• Periodical: Applied Mechanics and Materials (Volumes 373-375)
• Pages: 922-926
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.373-375.922
• Online since: August 2013
• Authors: Lin Wang, Ai Guo Li
• Keywords: Dynamic Accumulated Model, Flame Detection

References

[1] Yamagishi H, Yamaguchi J. Fire flame detection algorithm using a color camera [C]. ∥Proceedings of 1999 International Symposium on Micro-mechatronics and Human Science. Nagoya, Japan, 1999: 255-260.

DOI: 10.1109/mhs.1999.820014

[2] Yamagishi H, Yamaguchi J. A contour fluctuation data processing method for fire flame detection using a color camera [C]. ∥IEEE 26th Annual Conference on IECON of the Industrial Electronics Society, Nagoya, Japan, 2000, (2) : 824-829.

DOI: 10.1109/iecon.2000.972229

[3] Phillips W, Shah M, DaVitoria Lobo N. Flame recognition in video [C] ∥Fifth IEEE Workshop on Applications of Computer Vision. California: IEEE Press, 2000: 224-229.

DOI: 10.1109/wacv.2000.895426

[4] Xu Wei-sheng TIAN Chang-zheng FANG Sheng-ming. Fire Automatic Recognition Based on Image Visual Feature [J]. Computer Engineering, 2003, 29(18): 112-113, 191, In Chinese.

[5] Liu C B, Ahuja N. Vision based fire detection [C]/ 17th International Conference on Pattern Recognition (ICPR'04). Cambridge, United Kingdom: IEEE Press, 2004, 4: 134-137.

DOI: 10.1109/icpr.2004.1333722

[6] Chen T, Wu P, Chiou Y. An early fire-detection method based on image processing [C]/ International Conference on Image Processing. Singapore: IEEE Press, 2004, 3: 1707-1710.

DOI: 10.1109/icip.2004.1421401

[7] Yuan Fei-niu, Liao Guang-xuan, ZhangYong-ming. Feature Extraction for Computer Vision Based Fire Detection [J]. Journal of University of Science and Technology of China, 2006, 36 (1): 39-43, In Chinese.

[8] Osman Gunay, Kasım Tasdemir. Video based wildfire detection at night [J]. Fire Safety Journal, 2009, 44: 860-868.

[9] Juan Chen, Yaping He, Jian Wang. Multi-feature fusion based fast video flame detection [J]. Building and Environment, 2010, 45(5): 1113-1122.

DOI: 10.1016/j.buildenv.2009.10.017