基于动静态特征的监控视频火灾检测算法
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摘要
火灾是危害公共安全和社会发展的主要灾害之一,及时、准确的火灾报警具有重大意义。基于视频的火灾检测克服了传统技术的缺点,适应环境的能力较强。结合智能检测算法,其可以提供更直观、更丰富的火灾信息。所提算法分析了视频图像中的静态特征,得到疑似火焰图像,再通过动态特征进一步判断其是否为火焰。MATLAB仿真实验证明了该算法的有效性,并且其具有较好的实用性。
Fire is one of the most common hazards to public safety and social development,and timely and accurate fire alarm is of great significance.Video based fire detection overcomes the shortcomings of traditional technology and adapts to the various environment well.Combined with intelligent detection algorithm,it can provide more intuitive and richer fire information.The static characteristics of the video images are analyzed,and the suspected flame images are obtained,and then the flame is further judged by the dynamic characteristics.The effectiveness of the algorithm is proved by MATLAB in this paper and it has a good application prospect.
Fire is one of the most common hazards to public safety and social development,and timely and accurate fire alarm is of great significance.Video based fire detection overcomes the shortcomings of traditional technology and adapts to the various environment well.Combined with intelligent detection algorithm,it can provide more intuitive and richer fire information.The static characteristics of the video images are analyzed,and the suspected flame images are obtained,and then the flame is further judged by the dynamic characteristics.The effectiveness of the algorithm is proved by MATLAB in this paper and it has a good application prospect.
引文
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[2] ?ELIK T,DEMIREL H.Fire detection in video sequences using a generic color model[J].Fire Safety Journal,2009,44(2):147-158.
[3] HORNG W B,PENG J W,CHEN C Y.A new image-based real-time flame detection method using color analysis[C]//Networking,Sensing and Control,2005.IEEE,2005:100-105.
[4] LIU C B,AHUJA N.Vision Based Fire Detection[C]//International Conference on Pattern Recognition.IEEE Computer So-ciety,2004:134-137.
[5] T?REYIN B U,DEDEO,et al.Computer vision based method for real-time fire and flame detection[J].Pattern Recognition Letters,2006,27(1):49-58.
[6] JENIFER P.Effective visual fire detection in video sequences using probabilistic approach[C]//International Conference on Emerging Trands in Electrical & Computer Tehcnology.IEEE,2011.
[7] LAFARGE F,DESCOMBES X,ZERUBIA J.Textural kernel for SVM classification in remote sensing:application to forest fire detection and urban area extraction[C]//IEEE InternationalConference on Image Processing.IEEE,2005:III-1096-9.
[8] KO B C,CHEONG K H,NAM J Y.Fire detection based on vision sensor and support vector machines[J].Fire Safety Journal,2009,44(3):322-329.
[9] ZHAO J H,ZHANG Z,HAN S Z,et al.SVM based forest fire detection using static and dynamic features[J].Computer Science & Information Systems,2011,8(8):821-841.
[10] CHO B H,BAE J W,JUNG S H.Image Processing-Based Fire Detection System Using Statistic Color Model[C]//International Conference on Advanced Language Processing and Web Information Technology.IEEE,2008:245-250.
[11] SHAO J,WANG G,GUO W.An image-based fire detection method using color analysis[C]//International Conference on Computer Science and Information Processing.IEEE,2012:1008-1011.
[12] PéTERI R,FAZEKAS S,HUISKES M J.DynTex:A comprehensive database of dynamic textures[J].Pattern Recognition Letters,2010,31(12):1627-1632.
[13] 邵婧,王冠香,郭蔚.基于视频动态纹理的火灾检测[J].中国图象图形学报,2013,18(6):38-44.
[14] 许宏科,房建武,文常保.基于亮度与火焰区域边缘颜色分布的火焰检测[J].计算机应用研究,2010,27(9):3581-3584.