Development of Early Tunnel Fire Detection Algorithm Using the Image Processing
To avoid the large scale of damage of fire occurred in the tunnel, it is necessary to have a system to minimize and to discover the incident fast. However it is impossible to keep the human observation of CCTV in tunnel for 24 hour. So if the fire and smoke detection system through image processing warn fire state, it can be very convenient, and it can be possible to minimize damage even when people is not in front of monitor. In this paper, we proposed algorithm using the image processing, which is an early detection of the fire and smoke occurrence in the tunnel. The fire and smoke detection is different from the forest fire detection as there are elements such as car and tunnel lights and others that are different from the forest environment so that an indigenous algorithm has to be developed. The two algorithms proposed in this paper, are able to detect the exact position, at the earlier stay of detection. In addition, by comparing properties of each algorithm throughout experiment, we have proved the propriety of algorithm.
KeywordsDetection Algorithm Input Image Binary Image Color Information Difference Image
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- 1.Thou-Ho, C., Cheng-Liang, K., Sju-Mo, C.: An intelligent real-time fire-detection method based on video processing. In: IEEE 37th Annual 2003 International Carnahan Conference on Security Technology, Proceedings, October 14-16, 2003, pp. 104–111 (2003)Google Scholar
- 2.Cappellini, V., Mattii, L., Mecocci, A.: An intelligent system for automatic fire detection in forests. In: Third International Conference on Image Processing and its Applications, July 18-20, 1989, pp. 563–570 (1989)Google Scholar
- 3.Noda, S., Ueda, K.: Fire detection in tunnels using an image processing method. In: Vehicle Navigation and Information Systems Conference, August 31 - September 2,1994, pp. 57–62 (1994)Google Scholar
- 4.Cigada, A., Ruggieri, D., Zappa, E.: Road and railway tunnel fire hazard: a new measurement method for risk assessment and improvement of transit safety. In: Proceedings of the 2005 IEEE International Workshop on Measurement Systems for Homeland Security, Contraband Detection and Personal Safety Workshop (IMS 2005), March 29-30, 2005, pp. 89–94 (2005)Google Scholar
- 5.Koga, K., Inobe, T., Namai, T., Kaneko, Y.: Integrated traffic flow monitoring system in a large-scale tunnel. In: IEEE Conference on Intelligent Transportation System, ITSC 1997, November 9-12, 1997, pp. 165–170 (1997)Google Scholar
- 6.Yu, L., Wang, N., Meng, X.: Real-time forest fire detection with wireless sensor networks In: 2005 International Conference on Wireless Communications, Networking and Mobile Computing, Proceedings, September 23-26, 2005, vol. 2, pp. 1214–1217 (2005)Google Scholar