Research on improved edge extraction algorithm of rectangular piece

Yi-Bin He, Ya-Jun Zeng (), Han-Xin Chen, San-Xia Xiao (), Yan-Wei Wang () and Si-Yu Huang ()
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Yi-Bin He: School of Mechanical and Electrical Engineering, Wuhan Institute of Technology, Wuhan 430205, P. R. China†Hubei Provincial Key Laboratory of Chemical Equipment, Intensification and Intrinsic Safety, Wuhan 430205, P. R. China
Ya-Jun Zeng: School of Mechanical and Electrical Engineering, Wuhan Institute of Technology, Wuhan 430205, P. R. China
Han-Xin Chen: School of Mechanical and Electrical Engineering, Wuhan Institute of Technology, Wuhan 430205, P. R. China
San-Xia Xiao: #x2021;Library, Fujian Jiangxia University, Fuzhou 350108, P. R. China
Yan-Wei Wang: School of Mechanical and Electrical Engineering, Wuhan Institute of Technology, Wuhan 430205, P. R. China
Si-Yu Huang: #xA7;School of Mechanical and Electrical Engineering, Sanming University, Sanming 365004, P. R. China

International Journal of Modern Physics C (IJMPC), 2018, vol. 29, issue 01, 1-11

Abstract: Traditional edge detection operators such as Prewitt operator, LOG operator and Canny operator, etc. cannot meet the requirements of the modern industrial measurement. This paper proposes a kind of image edge detection algorithm based on improved morphological gradient. It can be detect the image using structural elements, which deals with the characteristic information of the image directly. Choosing different shapes and sizes of structural elements to use together, the ideal image edge information can be detected. The experimental result shows that the algorithm can well extract image edge with noise, which is clearer, and has more detailed edges compared with the previous edge detection algorithm.

Keywords: Mechanical measurement; morphology gradient; image edge detection; iterative threshold segmentation; image processing (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1142/S0129183118500079

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