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Power line detection based on symmetric partial derivative distribution prior
Cao YR(曹蔚然); Yang XY(杨秀义); Zhu LL(朱琳琳); Han JD(韩建达); Wang TR(王天然)
作者部门机器人学研究室
会议名称2013 IEEE International Conference on Information and Automation, ICIA 2013
会议日期August 26-28, 2013
会议地点Yinchuan, China
会议录名称2013 IEEE International Conference on Information and Automation, ICIA 2013
出版者IEEE Computer Society
出版地Washington, DC
2013
页码767-772
收录类别EI ; CPCI(ISTP)
EI收录号20140917372554
WOS记录号WOS:000346483800138
产权排序1
ISBN号978-1-4799-1334-3
关键词Aerial Images Image Priors Partial Derivatives Power Lines Prior Knowledge Radon Transform Radon Transformations Uavs
摘要In this paper, we propose a simple but effective image prior; symmetry partial derivative distribution to detect power lines in aerial image for UAVs. The symmetry partial derivative distribution is a kind of statistics of the images. It is based on a key observation; most nature images have symmetry partial derivative distributing. Based on this prior knowledge, we use radon transformation in partial derivative image and recognize the power lines in the aerial image. The experiment results demonstrate our method is effective for automatic power line detection.
语种英语
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被引频次:2[WOS]   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/14594
专题机器人学研究室
通讯作者Cao YR(曹蔚然)
作者单位1.Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China
2.Graduate School of the Chinese Academy of Sciences, Beijing, 100039, China
推荐引用方式
GB/T 7714
Cao YR,Yang XY,Zhu LL,et al. Power line detection based on symmetric partial derivative distribution prior[C]. Washington, DC:IEEE Computer Society,2013:767-772.
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