一种基于视觉的列车智能障碍物检测装置
Vision-based Train Intelligent Obstacle Detection Device
摘要
随着列车自动化程度的增加,列车智能障碍物检测变得越来越重要。本文运用图像处理技术,基于Journey2设计了一种非接触式列车智能障碍物检测装置。该装置可实现轨道线检测、障碍物识别、障碍物综合判断,可应用于城市轨道交通车辆非接触式障碍物检测。试验结果表明,其对障碍物的检测判断,准确度可达到99%。
作者
汪阳
戴林恩
Wang Yang;Dai Linen
出处
《艺术科技》
2020年第23期78-80,共3页
Art Science and Technology
二级参考文献19
-
1Clements Mair, Dr Saeed Fararooy. Practice and potential of computer vision for railways[ C]. Condition Monitoringtbr Rail Transport. lEE Seminar, 1998 Nov. 10.
-
2Jun Xue,Jun Cheng,Li Wang,et al. Visual monitoring- based railway grade crossing surveillance system [C]. 2008 Congress on Image and Signal Processing, 2008.
-
3Susumu Kubnta, Tsuyoshi Nakano, Yasukazu Okamoto. A global optimization algorithm for Real-time On-board stereo obstacle detection systems [C].Proceedings of the 2007 IEEE Intelligent Vehicles Symposium lstanbul, Turkey, 2007, June 13-15.
-
4-dayuki 'l-ugawa. Vision-based vehicles in Japan : Machine vision systems and driving control systems [J].IEEE Transactions on Industrial Electronics, 1994 vol. 41, August, 4.
-
5Fatih Kaleli, Yusuf Sinan Akgul. Vision-based railroad track extraction using dynamic programming [ C ]. Proceedings of the 12th International IEEE Conference on intelligent Transportation Systems, 2009, Oct. 3-7.
-
6Milan Ruder, Nikolaus Mohler, Faruque Ahmed. Anobstacle detection system [or automated train5[C]. Intelligent Vehicles Symposium, 2003.
-
7Maneesha Singh, Sameer Singh, Jay Jaiswal, el al. Autonomous rail track inspection using vision based system [ C ]. IEEE International Conference on Computational Intelligence Ibr Homeland Securily and Personal S',dety[ CI. 2006, Oct. 16-17.
-
8Canny J. A computational approach to e(Jge deteclJon [ J ]. IEEE Trans. Pattern Analysis and Machine Intelligence, 1986, 8(6) : 679-698.
-
9R Deriche. Using Canny's criteria to derive a recursively implemented optimal edge detector[J]. Computer Vision, 1987 Vol. 1, April, 167 187.
-
10N Cristianini, J Taylor. An introduction to support ve-:lor machines and other Kernel-based learning methods[M]. Cambridge UP, 2000.
共引文献49
-
1高浩荣.韩国“医药分离”改革面面观[J].半月谈,2000(5):36-37.
-
2段俊萍,彭梅.现代有轨电车工程的景观要求[J].都市快轨交通,2013,26(6):180-183. 被引量:4
-
3毛建华,宿亚军,袁向朗.创新理念,建立有轨电车科学发展模式[J].现代城市轨道交通,2014(1):29-32. 被引量:1
-
4李刚,李芾,文娟.中央导向胶轮轻轨车辆及其导向机理分析[J].国外铁道车辆,2014,51(4):19-23. 被引量:1
-
5王前选,梁习锋,刘应龙,鲁寨军,彭灿.铁路钢轨视觉识别检测方法[J].中南大学学报(自然科学版),2014,45(7):2496-2502. 被引量:23
-
6吴志勇,鞠传香.一种采用FPGA的轨道异物检测系统[J].山东理工大学学报(自然科学版),2015,29(2):9-13. 被引量:1
-
7史红梅,柴华,王尧,余祖俊.基于目标识别与跟踪的嵌入式铁路异物侵限检测算法研究[J].铁道学报,2015,37(7):58-65. 被引量:41
-
8何斌.现代有轨电车中压网络接线方案[J].都市快轨交通,2015,28(5):82-85. 被引量:3
-
9黄华文,刘伟铭,李军,谭飞刚,路新宇.地铁屏蔽门与车门间异物自动检测技术[J].铁路计算机应用,2015,24(12):62-65. 被引量:19
-
10肖虎,贺飞,朱冠宙.现代有轨电车轨道选型分析[J].技术与市场,2016,23(3):38-39. 被引量:2
-
1冯文海,詹前柱,张艳芳.同型半胱氨酸(Hcy)在原发性高血压患者中检测判断高血压病情的意义[J].临床医药文献电子杂志,2020,7(71):73-73.
-
2施泉,唐超.城市轨道交通车站客流时空分布特征分析--以南京地铁为例[J].综合运输,2020,42(7):12-17. 被引量:14
-
3李炎.软土地层顶管穿越复杂管线关键施工技术探讨[J].石家庄铁路职业技术学院学报,2020,19(3):31-35.
-
4宝蜂堂:致力打造蜂业领军品牌[J].党的生活(河南),2020(21).
-
5武国平,闫孝姮.露天矿用电缆卷放车智能保护系统设计[J].煤炭工程,2020,52(11):167-170. 被引量:3