Paper Title:
Research on Edge Detection of Thin Sheet Part Dimension Inspection System Based on Machine Vision
  Abstract

Aiming at the edge detection of thin sheet part dimension inspection system based on machine vision, a contrast research on edge detection is investigated. The Gaussian blurred simulation image and thin sheet part image are took as evaluation images, and the edge detection are done with Roberts operator, Sobel operator, Prewitt operator, Kirsch operator, Laplacian operator, LOG operator and mathematical morphology edge detection method. The results of edge detection are analyzed deeply, and the edge location accuracy, noise resisting ability and calculation time of each algorithm are compared. The single-pixel width connected contour is acquired with mathematical morphology edge detection method, the detection time are 0.0521 second and 0.457 second respectively. It is appropriate that taking the mathematical morphology edge detection method as the edge detection method of thin sheet part dimension inspection system based on machine vision.

  Info
Periodical
Edited by
Qiancheng Zhao
Pages
194-198
DOI
10.4028/www.scientific.net/AMM.103.194
Citation
J. G. Wu, K. F. He, B. Qin, "Research on Edge Detection of Thin Sheet Part Dimension Inspection System Based on Machine Vision", Applied Mechanics and Materials, Vol. 103, pp. 194-198, 2012
Online since
September 2011
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