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
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;
Conference_Titel :
Information and Automation (ICIA), 2013 IEEE International Conference on
Conference_Location :
Yinchuan
DOI :
10.1109/ICInfA.2013.6720397