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An algorithm for subpixel edge location of circular features based on Zernike moments and moment-preserving

  • Qingbin Tong*
  • , Xiaodong Zhang
  • , Zhenliang Ding
  • , Feng Yuan
  • *Corresponding author for this work
  • Beijing Jiaotong University
  • School of Electrical Engineering and Automation, Harbin Institute of Technology

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

Abstract

In order to satisfy the stringent requirements for the high accurate detection of circular feature in such applications as the vision measurement of electronic components and camera calibration, based on the principle of orthogonal Zernike moments and simple moment-preserving transform, a subpiexl edge detection algorithm for the curve of circular feasures is proposed. A circular-arc geometry is assumed for the boundary inside the detection area of template. The new arc-edge detector is designed as a cascade process using Zernike linear-edge detector and simple moment-preserving transform and a look-up table. The validity and detecting precision for the algorithm are studied. The experimental results show that the algorithm is very accurate and stable, and the measuring accuracy is better than 0.03 pixel. The proposed method is very effective in detecting circular features and as well ellipse curve for vision measurements.

Original languageEnglish
Title of host publicationInternational Conference on Image Processing and Pattern Recognition in Industrial Engineering
DOIs
StatePublished - 2010
Externally publishedYes
EventInternational Conference on Image Processing and Pattern Recognition in Industrial Engineering - Xi'an, China
Duration: 7 Aug 20108 Aug 2010

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7820
ISSN (Print)0277-786X

Conference

ConferenceInternational Conference on Image Processing and Pattern Recognition in Industrial Engineering
Country/TerritoryChina
CityXi'an
Period7/08/108/08/10

Keywords

  • Circular features
  • Edge location
  • Moment-preserving
  • Subpiexl
  • Zernike Moments

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