Yu CY, Fang J, Wang JJ, Zhang YM (2010) Video Fire Smoke Detection Using Motion and Color Features. Fire Technology 46(3), 651-663. [In English]

Web link: http://dx.doi.org/10.1007/s10694-009-0110-z

Keywords:

Video smoke detection, Fire detection, Motion features, Optical flow, Neural network, optical-flow, image

Abstract: A novel video smoke detection method using both color and motion features is presented. The result of optical flow is assumed to be an approximation of motion field. Background estimation and color-based decision rule are used to determine candidate smoke regions. The Lucas Kanade optical flow algorithm is proposed to calculate the optical flow of candidate regions. And the motion features are calculated from the optical flow results and use to differentiate smoke from some other moving objects. Finally, a back-propagation neural network is used to classify the smoke features from non-fire smoke features. Experiments show that the algorithm is significant for improving the accuracy of video smoke detection and reducing false alarms.