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Real-time multi-feature based fire flame detection in video

机译:视频中基于实时多特征的火焰检测

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In this study, the authors present a new approach to detect fire flame by processing and analysing the stationary camera videos. For a fire detection system, it is desired to be sensitive and reliable. The proposed method improves not only the sensitivity but also the reliability through reducing the susceptibility to false alarms. The proposed approach based on multi-feature, i.e. chromatic features, dynamic features, texture features, and contour features, can both improve the sensitivity and reliability in fire detection. In their approach, the authors adopt a novel algorithm to extract the moving region and analyse the frequency of flickers. Experimental results show that the proposed method can run in real-time and performs favourably against the state-of-the-art methods with higher accuracy in fire videos, lower false alarm rates in non-fire videos and faster response time.
机译:在这项研究中,作者提出了一种通过处理和分析固定摄像机视频来检测火焰的新方法。对于火灾探测系统,期望是灵敏且可靠的。所提出的方法通过减少对虚假警报的敏感性,不仅提高了灵敏度,而且还提高了可靠性。所提出的基于多种特征的方法,即色度特征,动态特征,纹理特征和轮廓特征,可以提高火灾探测的灵敏度和可靠性。在他们的方法中,作者采用了一种新颖的算法来提取运动区域并分析闪烁的频率。实验结果表明,所提出的方法可以实时运行,并且与最新技术相比具有良好的性能,在火灾视频中具有较高的准确性,在非火灾视频中具有较低的误报率,并且响应时间更快。

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