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Forest fire smoke detection based on video analysis


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Forest fire smoke detection based on video analysis
Zheng Huaibing1Zhai Jiyun2
1.Forest Fire Control Department,Nanjing Forest Police College,Nanjing 210023,China;
2.College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China
video analysis forest fire smoke detection Gaussian mixture model static features dynamic features support vector machine moving direction high frequency energy compactness
In order to improve the real-time and accuracy of fire smoke detection,a forest fire smoke detection method based on video analysis is proposed here.Gaussian mixture model is employed for background modeling,and moving target detection is conducted by the comparison with the background model.Multiple static and dynamic features are designed considering the characteristics of smoke.A classifier is designed based on a support vector machine to detect smoke from moving targets.Experiments are conducted for the normal case and foggy case.The results show that the proposed method can detect forest fire smoke effectively and is robust.The performances of different combinations of features are compared.The results show that the smoke recognition feature vector composed of moving direction,high frequency energy and compactness has the best performance,correct recognition rates are 92.7% in normal case and 76.3% in foggy case.


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Last Update: 2015-12-31