摘要
为了能够快速准确地检测到火焰,预防火灾的发生,提出了一种在Ohta颜色检测的基础上使用饱和度和Otsu阈值分割法相结合的算法。采用该算法可以实时、准确地检测出疑似火焰区域,然后对其进行圆形度、矩形度、重心高度系数特征分析,并结合LBP纹理分析,最后再通过SVM进行判定。实验结果表明,该算法能够准确地检测出火焰,且实时性和准确率都得到了显著提高。
Traditional fire detection methods utilize sensors to collect information on smoke particles, flame temperature and relative humidity, and then, evaluate and respond to fires. Since these sensors must be placed near the flame, the traditional detection methods cannot be used in scenes with extreme interference to the sensors. Besides,these traditional methods are also difficultly applied in large spaces, open spaces, and complex scenes. Especially, these traditional methods difficultly confirm descriptive information such as fire location, flame size, and fire development status and have low real-time performance and accuracy. In order to prevent the occurrence of fires, the flame should be detected quickly and accurately. Video flame detection is suitable for complex physical environments, and has low cost,high detection rate, and short response time. By analyzing the static and dynamic characteristics of the flame, this paper proposes an Ohta color space detection and combination of saturation with Otsu threshold segmentation method, which can effectively outline the possible region of flames in real time. By circularity, rectangularity, center-of-gravity-height coefficient, combining with LBP texture analysis, these regions can be featured and judged via SVM method. Finally, it is shown from experimental results that the proposed algorithm can accurately detect the flame and effectively improve the real-time performance and accuracy.
作者
刘佳丽
叶炯耀
LIU Jiali;YE Jiongyao(School of Information Science and Engineering,East China University of Science and Technology,Shanghai 200237,China)
出处
《华东理工大学学报（自然科学版）》
CAS
CSCD
北大核心
2019年第6期962-969,共8页
Journal of East China University of Science and Technology
