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Research on improved edge extraction algorithm of rectangular piece

Author

Listed:
  • 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)

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.

Suggested Citation

  • Yi-Bin He & Ya-Jun Zeng & Han-Xin Chen & San-Xia Xiao & Yan-Wei Wang & Si-Yu Huang, 2018. "Research on improved edge extraction algorithm of rectangular piece," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 29(01), pages 1-11, January.
    • Handle: RePEc:wsi:ijmpcx:v:29:y:2018:i:01:n:s0129183118500079
    DOI: 10.1142/S0129183118500079
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