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.

• Periodical: Applied Mechanics and Materials (Volume 103)
• Pages: 194-198
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.103.194
• Online since: September 2011
• Authors: Ji Gang Wu, Kuan Fang He, Bin Qin
• Keywords: Calculation Time, Edge Detection, Location Accuracy, Machine Vision Dimension Inspection System, Noise Resisting Ability

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