Laser Curve Extraction of Wheelset Based on Deep Learning Skeleton Extraction Network.

Journal: Sensors (Basel, Switzerland)
Published Date: Jan 23, 2022

Abstract

In this paper, a new algorithm for extracting the laser fringe center is proposed. Based on a deep learning skeleton extraction network, the laser stripe center can be extracted quickly and accurately. Skeleton extraction is the process of reducing the shape image to its approximate central axis representation while maintaining the image's topological and geometric shape. Skeleton extraction is an important step in topological and geometric shape analysis. According to the characteristics of the wheelset laser curve dataset, a new skeleton extraction network, a hierarchical skeleton network (LuoNet), is proposed. The proposed architecture has three levels of the encoder-decoder network, and YE Module interconnection is designed between each level of the encoder and decoder network. In the wheelset laser curve dataset, the F1_score can reach 0.714. Compared with the traditional laser curve center extraction algorithm, the proposed LuoNet algorithm has the advantages of short running time, high accuracy, and stable extraction results.

Authors

  • Shuai Luo
    School of Physical Science and Technology, Southwest Jiaotong University, Chengdu 610031, China.
  • Kai Yang
    Department of Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Lijuan Yang
    State Key Laboratory for Chemistry and Molecular Engineering of Medicinal Resources, School of Chemistry and Pharmaceutical Sciences, Guangxi Normal University, Guilin, 541004, China.
  • Yong Wang
    State Key Laboratory of Chemical Biology and Drug Discovery, Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University Hunghom Kowloon Hong Kong P. R. China kwok-yin.wong@polyu.edu.hk.
  • Xiaorong Gao
    3 Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, P. R. China.
  • Tianci Jiang
    School of Mechanical Engineering, Waseda University, Kitakyushu 8080135, Japan.
  • Chunjiang Li
    School of Mechanics, Zhejiang University, Hangzhou 310058, China.

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