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Overhead power line detection from UAV video images
Yang TW(杨唐文); Yin, Hang; Ruan QQ(阮秋琦); Han JD(韩建达); Qi JT(齐俊桐); Qin Y(秦勇); Wang, Zitong; Sun ZQ(孙增圻)
作者部门机器人学研究室
会议名称2012 19th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2012
会议日期November 28-30, 2012
会议地点Auckland, New zealand
会议录名称2012 19th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2012
出版者IEEE Computer Society
出版地Washington, DC, USA
2012
页码74-79
收录类别EI ; CPCI(ISTP)
EI收录号20131616212456
WOS记录号WOS:000320457300014
产权排序2
ISBN号978-0-4732-0485-3
关键词Power Line Detection Uav Image Binarization Hough Transform Fuzzy C-means Clustering Algorithm
摘要Currently, unmanned aerial vehicles (UAVs) are applied to routine inspection tasks of electric distribution networks. As an important information source, machine vision attracts much attention in the area of the UAV's autonomous control. To this end, real-time algorithms are studied in this paper to detect the power lines in the UAV video images. First, video images are converted into binary images through an adaptive thresholding approach. Then, Hough Transform is used to detect line candidates in the binary images. Finally, a fuzzy C-means (FCM) clustering algorithm is used to discriminate the power lines from the detected line candidates. The properties of power lines are used to remove the spurious lines, and the length and slope of the detected lines are used as features to establish the clustering data set. Experimental results show that the algorithms proposed are effective and able to tolerate noises from complicated terrain background and various illuminations.
语种英语
引用统计
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/20073
专题机器人学研究室
通讯作者Yang TW(杨唐文)
作者单位1.Beijing Key Laboratory of Advanced Information Science and Network Technology, Institute of Information Science, Beijing Jiaotong University, Beijing, 100044, China
2.State Key Laboratory of Robotics, Shenyang Institute of Automation, CAS, Shenyang, 110016, China
3.Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China
4.Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
推荐引用方式
GB/T 7714
Yang TW,Yin, Hang,Ruan QQ,et al. Overhead power line detection from UAV video images[C]. Washington, DC, USA:IEEE Computer Society,2012:74-79.
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