Motion deblurring for a power transmission line inspection robot

  • Authors:

  • Siyao Fu;Yunchu Zhang;Xiaoguang Zhao;Zize Liang;Zengguang Hou;Anmin Zou;Min Tan;Wenbo Ye;Lian Bo

  • Affiliations:

  • Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, The Chinese Academy of Sciences, Beijing, China;Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, The Chinese Academy of Sciences, Beijing, China and School of Information and Electric Eng., Shandong Univ. of ...;Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, The Chinese Academy of Sciences, Beijing, China;Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, The Chinese Academy of Sciences, Beijing, China;Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, The Chinese Academy of Sciences, Beijing, China;Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, The Chinese Academy of Sciences, Beijing, China;Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, The Chinese Academy of Sciences, Beijing, China;Zunyi Power Supply Bureau, Guizhou Power Grid Corporation, Zunyi, China;Zunyi Power Supply Bureau, Guizhou Power Grid Corporation, Zunyi, China

  • Venue:
  • ICIC'06 Proceedings of the 2006 international conference on Intelligent computing: Part II
  • Year:
  • 2006

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Abstract

Inspection robot must detect the obstacles from the complex background according to their types when it is crawling along the power transmission line in order to negotiate reliably. In ideal cases, robot's vision system can give satisfactory results, however, motion blur due to camera motion caused by wind or other unknown causes can significantly degrade the quality of the image acquired. It is an undesired effect. In this paper, a complete motion deblurring procedure for obstacle images has been proposed, we try to analyze the running environment of the robot to develop the model of the motion blur. The acquired motion blur information is used to identify the point spread function (PSF) as well as restore the blurred image at the same time. Experiments on real blurred images on power transmission line prove the feasibility and reliability of this algorithm.