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A Color Flame Region Segmentation Method Using Temperature Distribution Characteristics of Flame  

Lee, Hyun-Sul (공주대학교 전기전자제어공학부)
Kim, Won-Ho (공주대학교 전기전자제어공학부)
Publication Information
Journal of Satellite, Information and Communications / v.9, no.2, 2014 , pp. 33-37 More about this Journal
Abstract
This paper propose a method to sort flame regions and non-flame regions in a color image based on temperature Characteristics of flame. The traditional algorithms simply detect flame regions those are colored between yellow and red and there are lot of false detection in this method. But the colors of real flame are fallen between white and red and flame color variation over the flame. In this paper, it reduce false detection by separating colors according to temperature Characteristics of flame. The proposed method firstly finds a color model to express the temperature Characteristics of fire and then the color model is non-linearly quantized based on color values and analyzed using histogram and finally detect the candidate flame regions. The proposed method has 71.8% of matching rate and if it is compared with non-matching rate of traditional algorithms, the non-matching rate is improved by 27 times than others.
Keywords
Video Surveillance; Flame detection; Color Analysis; Image Processing; Digital signal processing;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 Dong-Yol Yun, Sung-Ho Kim, "A Design of Fire Monitoring System Based On Unmaned Helicopter and Sensor Network", Korea Institute of Intelligent Systems, Vol. 17, pp. 173-178, 2007
2 Yong-Woo Kim, Do-Hyeon Kim, Ho-Young Kwak, Hee-Dong Park, "A Study of Fire Shunt Guidance Based on Wireless Sensor Network", Korea Multimedia Society, Vol. 11, pp 1547-1554, 2008
3 Turgay Celik,"Fast and Efficient Method for Fire Detection Using Image Processing", ETRI Journal, vol. 32, pp 881-890, 2010   DOI
4 Turgay Celik, Hasan Demirel, Huseyin Ozkaramanli, Mustafa Uyguroglu, "Fire detection using statistical color model in video sequences", ELSEVIER, Journal of Visual Communication & Image Representation, Vol. 18, pp. 176-185, 2007   DOI   ScienceOn
5 Tai Yu Lai, Jong Yih Kuo, Yong-Yi FanJiang, Shang-Pin Ma, Yi Han Liao, "Robust Little Flame Detection on Real-Time Video Surveillance System", IEEE Third International Conference on Innovations in Bio-Inspired Computing and Applications, pp 139-143, 2012
6 Dengyi Zhang, Shizhong Han, Jianhui Zhao, Zhong Zhang, Chengzhang Qu, Youwang Ke, Xiang Chen, "Image Based Forest Fire Detection Using Dynamic Characteristics With Artificial Neural Networks" IEEE International Joint Conference on Artificial Intelligence, pp. 290-293, 2009
7 Chen Juan, Bao Qifu, "Digital image processing based fire flame color and oscillation frequency analysis", ELSEVIER, Procedia Engineering, vol. 45, pp 595-601, 2012   DOI   ScienceOn
8 Juan Chen, Yaping He, Jian Wang "Multi-feature fusion based fast video flame detection", Building and Environment, vol. 45, pp 1113-1122, 2010   DOI   ScienceOn
9 B.U. Toreyin, Y. Dedeoglu, and A.E. Cetin," Flame Detection in Video Using Hidden Markov Models," in IEEE International Conference on Image Processing, vol.2, pp. 1230-1233, 2005.
10 누완, 이현술, 김원호, "점멸성 비화염 검출을 제거하는 웨이 블릿변환 기반의 컬러영상 화염 검출 방법", 통신위성우주산업연구회논문지, vol. 8, no. 4, pp. 89-94, 2013