Acta Optica Sinica, Volume. 43, Issue 19, 1912002(2023)

Multilayer Perceptron-Based Fusion Method for Metal Surface Measurement Data by Multi-Sensors Incorporating Photometric Stereo and Structured Light

Yuansong Yang, Xi Wang, and Mingjun Ren*
Author Affiliations
  • School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
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    Figures & Tables(19)
    Schematic of fringe projection system
    Schematic of photometric stereo vision network
    Flowchart of multimodal data fusion
    Schematic of depth gradient
    Schematic of proposed network structure
    Schematic of network sampling policy
    Overall diagram of experiment equipment
    Simulation results. (a) Simulation normal image; (b) simulation depth image; (c) result of fusion algorithm; (d) result of normal integrity algorithm
    Mean error results along Z-axis of different algorithms. (a) (b) 3D distribution; (c) (d) 2D distribution
    Mean error results along Z-axis of different algorithms under different noise levels. (a) Fusion algorithm; (b) normal integrity algorithm
    Comparison of mean error along Z-axis by different noise level
    Experiment parts
    Normal vector results. (a) Result of part 1 by deep learning method; (b) result of part 1 by least square method; (c) result of part 2 by deep learning method; (d) result of part 2 by least square method
    Experimental results of part 1 and part 2. (a)(b) Structured light reconstruction results; (c)(d) fusion reconstruction results by least square normal vector; (e)(f) integration algorithm reconstruction results; (g)(h) reconstruction results by proposed method
    Error distribution results. (a) Structured light method result of part 1; (b) fusion algorithm result of part 1; (c) structured light method result of part 2; (d) fusion algorithm result of part 2
    • Table 1. Relationship between μ and measurement error of normal vector angle

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      Table 1. Relationship between μ and measurement error of normal vector angle

      μ0.010.030.050.10
      Normal noise /(°2347.5
    • Table 2. Comparison of mean error along Z-axis under different noise levels

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      Table 2. Comparison of mean error along Z-axis under different noise levels

      μ00.010.030.050.10
      Fusion algorithm0.00250.00620.01930.03360.1288
      Integrity algorithm0.00230.18510.54450.88841.6980
    • Table 3. Repetitive measurement accuracy (RMS) of fusion point clouds

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      Table 3. Repetitive measurement accuracy (RMS) of fusion point clouds

      No.123456789
      Cylinder2.02.31.22.12.43.72.92.93.4
      Quadric1.41.40.61.00.70.71.41.00.9
    • Table 4. RMS error of different methods

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      Table 4. RMS error of different methods

      SurfaceCMMStructured light methodFusion algorithm
      Cylinder35156113
      Quadric75188131
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    Yuansong Yang, Xi Wang, Mingjun Ren. Multilayer Perceptron-Based Fusion Method for Metal Surface Measurement Data by Multi-Sensors Incorporating Photometric Stereo and Structured Light[J]. Acta Optica Sinica, 2023, 43(19): 1912002

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    Paper Information

    Category: Instrumentation, Measurement and Metrology

    Received: Feb. 3, 2023

    Accepted: Apr. 20, 2023

    Published Online: Oct. 13, 2023

    The Author Email: Mingjun Ren (renmj@sjtu.edu.cn)

    DOI:10.3788/AOS230497

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