改进MOG-LRMF 的铁轨动态异物检测

交通运输系统工程与信息 ›› 2020, Vol. 20 ›› Issue (2): 91-100.

• 智能交通系统与信息技术 • 上一篇下一篇

改进MOG-LRMF 的铁轨动态异物检测

侯涛^{* a}，伍海萍^a，牛宏侠^b

兰州交通大学a. 自动化与电气工程学院；b. 自动控制研究所，兰州 730070

收稿日期:2019-11-15 修回日期:2020-01-30 出版日期:2020-04-25 发布日期:2020-04-30
作者简介:侯涛(1975-)，男，四川中江人，教授，博士.
基金资助:
兰州交通大学“百名青年优秀人才培养计划”基金/ Foundation of A Hundred Youth Talents Training Program of Lanzhou Jiaotong University(2018-103).

Real-time Detection of Rail Dynamic Foreign Object Intrusion Based on Improved MOG-LRMF

HOU Tao^a, WU Hai-ping^a, NIU Hong-xia^b

a. School of Automation and Electrical Engineering; b. Automatic Control Research Institute, Lanzhou Jiaotong University, Lanzhou 730070, China

Received:2019-11-15 Revised:2020-01-30 Online:2020-04-25 Published:2020-04-30

摘要/Abstract

摘要：

针对复杂铁路环境下动态入侵异物检测精度低和抗扰能力差等问题，提出一种基于改进MOG-LRMF算法的铁路轨道异物入侵实时检测方法. 引入仿射变换，对视频序列可能出现的抖动进行预校正处理；分析MOG-LRMF模型特点，利用MOG模型对视频帧中的背景进行建模，用前一帧背景中学习到的知识对当前帧背景进行预测，优化MOG-LRMF参数求解模型；利用EM算法对改进MOG-LRMF模型进行参数求解，实现背景在线实时更新. 实验结果表明，改进的MOG-LRMF算法在光照充足、光线较弱、相机存在抖动、背景复杂及存在多个目标情形下都能提高目标检测精度，具有较好的抗干扰性、鲁棒性和快速性.

关键词: 信息技术, 异物检测, 改进MOG-LRMF, 仿射变换, EM算法

Abstract:

To address the issues of low detection accuracy and poor anti- interference ability for the dynamic intrusion of foreign objects in complex rail environments, a real-time detection method for foreign object intrusion in railway track based on improved MOG- LRMF algorithm is proposed in this paper. Firstly, the affine transformation is used to pre-correct video sequences. Then, the background of the frame in a video sequence is predicted with the background knowledge learned in the previous frame to improve the MOG-LRMF model by analyzing the characteristics of the MOG-LRMF model. Finally, the EM algorithm is used to solve the parameters of the MOG-LRMF model, and it can realize the online real-time update of the background. The experiment results show that the improved MOG-LRMF algorithm can greatly enhance the target detection accuracy under sufficient illumination, weak light, camera jitter, complex environment, and multiple targets. Moreover, the improved MOGLRMF algorithm has better anti-interference, robustness, and rapidity.

Key words: information technology, foreign object detection, improved MOG-LRMF, affine transformation, EM algorithm

中图分类号:

TP391.9

侯涛，伍海萍，牛宏侠. 改进MOG-LRMF 的铁轨动态异物检测[J]. 交通运输系统工程与信息, 2020, 20(2): 91-100.

HOU Tao, WU Hai-ping, NIU Hong-xia. Real-time Detection of Rail Dynamic Foreign Object Intrusion Based on Improved MOG-LRMF[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(2): 91-100.

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改进MOG-LRMF 的铁轨动态异物检测

Real-time Detection of Rail Dynamic Foreign Object Intrusion Based on Improved MOG-LRMF

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