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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)
Department机器人学研究室
Conference Name2013 IEEE International Conference on Information and Automation, ICIA 2013
Conference DateAugust 26-28, 2013
Conference PlaceYinchuan, China
Source Publication2013 IEEE International Conference on Information and Automation, ICIA 2013
PublisherIEEE Computer Society
Publication PlaceWashington, DC
2013
Pages767-772
Indexed ByEI ; CPCI(ISTP)
EI Accession number20140917372554
WOS IDWOS:000346483800138
Contribution Rank1
ISBN978-1-4799-1334-3
KeywordAerial Images Image Priors Partial Derivatives Power Lines Prior Knowledge Radon Transform Radon Transformations Uavs
AbstractIn 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.
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/14594
Collection机器人学研究室
Corresponding AuthorCao YR(曹蔚然)
Affiliation1.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
Recommended Citation
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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