DocumentCode
3006634
Title
Power line detection based on symmetric partial derivative distribution prior
Author
Weiran Cao ; Xiuyi Yang ; Linlin Zhu ; Jianda Han ; Tianran Wang
Author_Institution
Key Lab. of Robot., Shenyang Inst. of Autom., Shenyang, China
fYear
2013
fDate
26-28 Aug. 2013
Firstpage
767
Lastpage
772
Abstract
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.
Keywords
Radon transforms; autonomous aerial vehicles; object recognition; power engineering computing; power overhead lines; Radon transformation; UAV; aerial image; automatic power line detection; partial derivative image; symmetric partial derivative distribution prior; Automation; Image edge detection; Inspection; Laboratories; Surveillance; Transforms; Power line detection; Radon transforms; Symmetry partial derivative distribution; UAVs;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Automation (ICIA), 2013 IEEE International Conference on
Conference_Location
Yinchuan
Type
conf
DOI
10.1109/ICInfA.2013.6720397
Filename
6720397
Link To Document