A Real-Time Fire Detection Method from Video with Multifeature Fusion. (14th July 2019)

• Record Type: Journal Article
• Authors: Gong, Faming; Li, Chuantao; Gong, Wenjuan; Li, Xin; Yuan, Xiangbing; Ma, Yuhui; Song, Tao
• Other Names: Versaci Mario Academic Editor.
• Is Part Of: Computational intelligence and neuroscience. Volume 2019(2019)
• Publication Date: 2019-07-14
• Subjects: Neurosciences -- Data processing -- Periodicals; Computational intelligence -- Periodicals; Computational neuroscience -- Periodicals; 612.80285
• DOI: 10.1155/2019/1939171
• Languages: English
• ISSNs: 1687-5265

Abstract

Abstract : The threat to people's lives and property posed by fires has become increasingly serious. To address the problem of a high false alarm rate in traditional fire detection, an innovative detection method based on multifeature fusion of flame is proposed. First, we combined the motion detection and color detection of the flame as the fire preprocessing stage. This method saves a lot of computation time in screening the fire candidate pixels. Second, although the flame is irregular, it has a certain similarity in the sequence of the image. According to this feature, a novel algorithm of flame centroid stabilization based on spatiotemporal relation is proposed, and we calculated the centroid of the flame region of each frame of the image and added the temporal information to obtain the spatiotemporal information of the flame centroid. Then, we extracted features including spatial variability, shape variability, and area variability of the flame to improve the accuracy of recognition. Finally, we used support vector machine for training, completed the analysis of candidate fire images, and achieved automatic fire monitoring. Experimental results showed that the proposed method could improve the accuracy and reduce the false alarm rate compared with a state-of-the-art technique. The method can be applied to real-time camera monitoring systems, such as home security, forest fire alarms, and commercial monitoring.