摘要
提出了一种基于图像熵的烟雾运动模式识别方法,用来实现对火灾烟雾的探测.通过对烟雾自由扩散模型的理论分析,得出了烟雾扩散熵增运动的特征.通过引入信号学中"图像熵"的理论,用来捕捉烟雾运动造成的熵变特征,进而实现火灾烟雾的检测.经过实验的验证和分析,并对图像熵值的变化进行傅立叶变换,得出了干扰运动和烟雾运动具有不同特征信号的结论,从而实现了烟雾的识别.与以往研究者通过研究视频烟雾的图像特征出发不同,文中从烟雾的热力学的性质和它在流体力学方面的运动特征,得出它与一般的刚体具有截然不同的运动模式的理论,以图像熵作为核心参量,得出一种实用高效的火灾烟雾检测算法.实验表明:这种检测算法受到环境的干扰较小,特别适合复杂环境的烟雾检测,并可以用于对火灾环境的评估.
Fire smoke recognition is of great significance for monitoring fire disasters. This paper proposes a new smoke movement recognition method which is based on image entropy to realize the detection of fire smoke. Through the theoretical analysis of free diffusion model of smoke, the conclusion is drawn that the diffusion of smoke is a kind of entropy-increasing movement. By introducing the concept of ＂image entropy＂, which is nor- mally used in signature analysis, to capture the features of entropy changing, we can realize the detection of fire smoke. Through the experiment and analysis and by using Fourier transform on the changes of image entropy, a conclusion is drawn that interference movement and smoke movement are two kinds of deferent movement pat- tern. In this way, we can realize the recognition of smoke. Unlike researchers who study the characteristics of smoke image to detect smoke, we analyze the thermodynamic properties and fluid mechanic properties of smoke. We conclude that the smoke movement pattern is different from other rigid movement pattern. By using the image entropy as the core parameter, we get a simple and high efficient algorithm to detect the smoke. Experiment shows that the detection algorithm has much less interference from the surroundings. It is especially proper to be used in complex environment. It can also be used as an evaluation algorithm of fire disaster environment.
出处
《江苏科技大学学报（自然科学版）》
CAS
北大核心
2015年第1期52-57,共6页
Journal of Jiangsu University of Science and Technology:Natural Science Edition
基金
江苏省高校科研成果产业化推进基金资助项目(JHB2011-41)
关键词
火灾烟雾识别
图像熵
烟雾运动模式
熵增运动
fire smoke recognition
image entropy
movement pattern of smoke
entropy increasing movement
