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题名: Power line detection based on symmetric partial derivative distribution prior
作者: 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: 2013 IEEE International Conference on Information and Automation, ICIA 2013
会议录出版者: IEEE Computer Society
会议录出版地: Washington, DC
出版日期: 2013
页码: 767-772
收录类别: EI
ISBN号: 9781479913343
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
产权排序: 1
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/14594
Appears in Collections:机器人学研究室_会议论文

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Recommended Citation:
曹蔚然; 杨秀义; 朱琳琳; 韩建达; 王天然; .Power line detection based on symmetric partial derivative distribution prior.见:IEEE Computer Society.2013 IEEE International Conference on Information and Automation, ICIA 2013,Washington, DC,2013,767-772
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文件名: Power line detection based on symmetric partial derivative distribution prior.pdf
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