A fast subpixel edge detection method for image of micro-part

Tao Zeng, Gengchen Shi, Bing Zhang, Zhen Wang, Fang Yang

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

Abstract

In order to quickly and exactly detect the subpixel image edge of micro-part, a fast subpixel edge detection method based on the property of Gaussian blurred edge model is proposed. Firstly, the approximate positioning of edge point was extracted by double-threshold segmentation; secondly a Zernike moment operator with a mask size of 5×5 was used to get rid of false edge points and relocate the edge with subpixel accuracy. Experiment results show that the subpixel accuracy and the running time of the method are 0.16 pixel and 0.94s. Therefore, the method is suitable for online threedimensional size detection of micro-part.

Original languageEnglish
Title of host publicationFifth International Conference on Machine Vision, ICMV 2012
Subtitle of host publicationComputer Vision, Image Analysis and Processing
DOIs
Publication statusPublished - 2013
Event5th International Conference on Machine Vision: Computer Vision, Image Analysis and Processing, ICMV 2012 - Wuhan, China
Duration: 20 Oct 201221 Oct 2012

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8783
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference5th International Conference on Machine Vision: Computer Vision, Image Analysis and Processing, ICMV 2012
Country/TerritoryChina
CityWuhan
Period20/10/1221/10/12

Keywords

  • Double-threshod segmentation
  • Micro-gear image
  • Subpixel edge
  • Zernike moment operator

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