Surface Quality Detection of Welding Nuts Based on Machine Vision

Zheng Li; Li Xin Lu; Gui Qin Li; Yan Zhao; Hong Bo Li; Xiao Yuan

doi:10.4028/www.scientific.net/AMR.1039.237

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 1039Surface Quality Detection of Welding Nuts Based on...

Surface Quality Detection of Welding Nuts Based on Machine Vision

Abstract:

Welding nuts are being used widely in automotive industry as threaded fasteners, its security and reliability requests are increasingly high. Accurate and quick detection results for surface quality can be obtained by using machine vision. Image edge detection by Canny operator has stronger acclimatization in anti-jamming and accurate edge localization. In order to suppress noise in maximum, an improved method is put forward to calculate the gradient of Canny operator, introducing Robert cross gradient in 3×3 neighborhood when calculating the gradient magnitude in finite difference method. The experimental results show that the improved Canny operator makes more effectively on the surface detection of welding nuts.

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Periodical:

Advanced Materials Research (Volume 1039)

Pages:

237-241

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1039.237

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Online since:

October 2014

Authors:

Zheng Li, Li Xin Lu*, Gui Qin Li, Yan Zhao, Hong Bo Li, Xiao Yuan

Keywords:

Canny Operator, Machine Vision, Surface Detection, Welding Nuts

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* - Corresponding Author

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