WU Xiyin,YAN Yunyang,DU Jing,et al.Fire detection based on fusion of multiple features[J].CAAI Transactions on Intelligent Systems,2015,10(02):240-247.[doi:10.3969/j.issn.1673-4785.201406022]





Fire detection based on fusion of multiple features
吴茜茵12 严云洋12 杜静12 高尚兵2 刘以安1
1. 江南大学 物联网工程学院, 江苏 无锡 214122;
2. 淮阴工学院 计算机工程学院, 江苏 淮安 223003
WU Xiyin12 YAN Yunyang12 DU Jing12 GAO Shangbing2 LIU Yi’an1
1. School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China;
2. Faculty of Computer Engineering, Huaiyin Institute of Technology, Huaian 223003, China
feature extractionfeature fusionsupport vector machinecolor modelfire detectioncircularity measuresrectangularityorthocenter height
Video fire detection is an important method to prevent fire disaster under complex circumstances. In order to improve the efficiency and robustness of fire detection, the color feature model can be improved based on RGB and HSI color space and the suspected flame area is extracted effectively. After analysis on the experimental results with different features of shape or structure of fire and the influence of their combined features on the validity of fire detection, a method of flame detection is proposed based on fusion of circularity, rectangularity and the coefficient of orthocenter height. Based on fusion of these flame features, the support vector machine (SVM) is used for classification. Experimental results on the fire videos at Bilkent University show that the proposed algorithm is efficient and fast for fire detection, and it could detect fire real-time under a variety of circumstances.


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更新日期/Last Update: 2015-06-15