基于显著性检测的红外森林火灾监测系统
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摘要
为了实现森林火灾的有效监测,设计了基于显著性检测的红外森林火灾监测系统。该系统通过固定在360°旋转云台上的红外相机采集图像,针对采集到的图像帧通过基于引导滤波的改进Frequency-tuned(FT)算法进行显著性区域提取,对其进行疑似火灾区域分割、特征提取及干扰源排除等处理,以检测并识别目标物。实验结果表明,该系统能准确检测出森林中的火焰,尤其是火灾的早期微小火焰。系统具有检测视场广和实时性高的特点,能为类似火灾监控系统的开发及实现提供技术指导。
In order to realize the effective monitoring of forest fires,an infrared forest fire monitoring system based on saliency detection was designed. The system acquires images by an infrared camera fixed on a 360° rotating pan/tilt, performs significant region extraction for the image frame by improved filtering-tuned(FT) algorithm based on the guided filtering,and processes suspected fire area segmentation, feature extraction and interference source exclusion to detect and identify the target. The experimental results showed that the system can accurately detect the fire flame in the forest, especially the small flame in the early stage of the fire. At the same time, the system has the characteristics of wide field of view and high real-time performance, and can provide technical guidance for the development and implementation of similar fire monitoring systems.
In order to realize the effective monitoring of forest fires,an infrared forest fire monitoring system based on saliency detection was designed. The system acquires images by an infrared camera fixed on a 360° rotating pan/tilt, performs significant region extraction for the image frame by improved filtering-tuned(FT) algorithm based on the guided filtering,and processes suspected fire area segmentation, feature extraction and interference source exclusion to detect and identify the target. The experimental results showed that the system can accurately detect the fire flame in the forest, especially the small flame in the early stage of the fire. At the same time, the system has the characteristics of wide field of view and high real-time performance, and can provide technical guidance for the development and implementation of similar fire monitoring systems.
引文
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[2]辛颖,李禹洁,邢美净.基于红外图像的森林凋落物阴燃火灾探测[J].消防科学与技术,2018,37(1):61-64.
[3]陈凯,孙德新,刘银年.应用于森林火灾监测的中波红外相机设计[J].红外技术,2016,38(6):514-518.
[4]余阳,赵海龙,韩来君.基于红外热成像的山火识别技术研究[J].现代电子技术,2017,40(24):77-79+84.
[5]仲亭玉,刘文萍,刘鹏举.基于分数阶微分视频融合的森林烟火检测算法[J].北京林业大学学报,2017,39(3):24-31.
[6]王景华,龙先华,李德,等.基于GIS的四川省森林火灾空间分布特征[J].东北林业大学学报,2012,40(9):51-56.
[7]朱玉军.森林火灾危险性分析与防火建议[J].消防科学与技术,2017,36(6):867-870.
[8]胡燕,王慧琴,张国飞,等.基于视频图像的远程火灾探测系统[J].计算机工程,2013,39(3):279-284.
[9]朱磊.基于图像增强与多特征的森林火灾烟雾检测算法[J].消防科学与技术,2018,37(2):225-228.
[10]陈志谦,王毅.全视场人工智能火灾探测系统分析[J].消防科学与技术,2017,36(10):1409-1411.
[11]毕振波,乐天,潘洪军,等.图像型火灾探测预处理方法综述[J].消防科学与技术,2016,35(1):87-91.