• 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