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Application of neural network on distortion correction based of standard grid

  • Hongping Wang
  • , Guohua Cao
  • , Hongji Xu
  • , Peng Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Image interpretation must obtain accurate position of image, but those questions, brought by angle of imaging equipment placed and camera lens deviation, induce nonlinear geometry distortion of image. The paper proposes the method that utilizes neural network to achieve the correction of geometry distortion of standard grid on the basis of grid image for extracting available exact information of image. The method makes use of least square procedure to obtain measured data and distortion data on the basis of grid plate centre, and uses BP neural network to gain correcting model and then obtain true value of optional point on image. It overcomes the shortcoming of interpolation that can not describe nonlinear distortion, and precision is less than 0.001mm.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009
Pages2717-2722
Number of pages6
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009 - Changchun, China
Duration: 9 Aug 200912 Aug 2009

Publication series

Name2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009

Conference

Conference2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009
Country/TerritoryChina
CityChangchun
Period9/08/0912/08/09

Keywords

  • Correction
  • Geometry distortion
  • Grid image
  • Neural network

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