摘要
针对传统火灾探测存在反应滞后,误报率高等问题,提出一种基于多传感器融合的火灾识别算法。采用运动和颜色检测提取可见光图像的疑似火灾区域,同时采用阈值分割提取红外图像的疑似火灾区域。将两者疑似火灾区域分别进行特征提取,再根据所获特征进行基于SVM的融合火灾识别,通过传感器检测实时的温度与烟雾浓度,从而实现可靠和快速的火灾识别。实验结果表明,该火灾识别算法在可接受的时间范围内准确率高且鲁棒性强。
Aiming at the delayed response and missing alarm problems of traditional fire detection,we propose a fire detection algo⁃rithm based on multi-sensor fusion.Firstly,a algorithm combined with motion detection and color detection is adopted to extract the candidate fire regions of visible light images and a threshold segmentation algorithm is used to extract the candidate fire regions of infrared images.Secondly,the algorithm extracts the dynamic and static characteristics of both candidate fire regions.Finally,the fusion fire identification based on SVM is adopted accroding to the acquired features and the real-time temperature and smoke concentration are detected by sensor simultaneously to achieve reliable and rapid fire detection.Experimental results indicate that the pro⁃posed algorithm has high accuracy and robustness in an acceptable time range.
作者
陈培豪
肖铎
李晨辉
CHEN Pei-hao;XIAO Duo;LI Chen-hui(City College,Zhejiang University,Zhejiang Hangzhou 310015,China;College of Control Science and Engineering,Zhejiang University,Zhejiang Hangzhou 310027,China)
出处
《消防科学与技术》
CAS
北大核心
2020年第6期810-813,共4页
Fire Science and Technology
基金
浙江省重点研发计划项目(2019C01150)
杭州市科技计划项目(20170533B19)。
