摘要
针对机场、油库等特定区域的高识别率、低误报率入侵事件监控需求,提出了一种基于光纤传感与红外视频的目标识别方法。其中,光纤传感部分采用基于MCSVM的非对称双马赫-曾德尔干涉仪(ADMZI)分布式光纤振动传感器,将EMD(经验模式分解)、将峰度特征与MCSVM相结合以提高识别率;红外识别部分将灰度差值图像通过小波变换提高清晰度。两者经过模式对比算法,实现入侵事件判定。搭建系统做现场实验,结果表明:该方法能够识别四种常见的入侵事件(爬越围栏、敲击电缆、剪断围栏、摇动围栏),平均识别率在92.5%以上,误报率0.9%,相对传统单一传感器方案,该方法在漏报率和虚警率等系统性能上都有较大的改善,能够满足实际应用要求。
To meet the requirements of intrusion detection with high recognition rate and low false alarm rate in specific areas such as airports and oil depots,a target recognition method based on optical fiber sensing and infrared video was proposed.Among them,the distributed optical fiber vibration sensor based on MCSVM ADMZI(asymmetric dual Mach-Zehnder interferometer)was used in the optical fiber sensing part,which combined the empirical mode decomposition(EMD)and the kurtosis feature with the MCSVM to improve the recognition rate.The infrared recognition part improved the clarity of the gray difference image through the wavelet transform.The intrusion detection was realized by pattern comparison algorithm.The field experiment results show that this method can identify four common intrusion events(climbing fence,tapping cable,cutting fence,shaking fence).The average recognition rate is over 92.5%,and the false alarm rate is 0.9%.Compared with the traditional single sensor scheme,this method has a great improvement in the system performance such as false alarm rate and false alarm rate,and can meet the practical application requirements.
作者
安建昌
江俊峰
徐中原
朱万山
王进
刘铁根
刘琨
An Jianchang;Jiang Junfeng;Xu Zhongyuan;Zhu Wanshan;Wang Jin;Liu Tiegen;Liu Kun(Institute of Optical Fiber Sensing of Tianjin University,Key Laboratory of Opto-Electronics Information Technology,School of Precision Instrument&Opto-Electronics Engineering,Tianjin University,Tianjin 300072,China;Tianjin Port Branch of Tianjin Binhai New District Public Security Burea,Tianjin 300456,China)
出处
《红外与激光工程》
EI
CSCD
北大核心
2020年第5期170-176,共7页
Infrared and Laser Engineering
基金
国家自然科学基金(61475114,61405139,61227011,61378043,61505138)
国家重大科学仪器设备开发专项(2013YQ030915)。
关键词
入侵事件监测
光纤振动传感
红外识别
复合技术
intrusion event monitoring
optical fiber vibration sensor
infrared recognition
composite technology
