• Laser & Optoelectronics Progress
  • Vol. 59, Issue 14, 1415018 (2022)
Dongyun Lin1, Jiaqi Lu1, Chunming Li2,*, and Xiafu Peng1
Author Affiliations
  • 1School of Aerospace Engineering, Xiamen University, Xiamen 361100, Fujian , China
  • 2School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 610000, Sichuan , China
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    DOI: 10.3788/LOP202259.1415018 Cite this Article Set citation alerts
    Dongyun Lin, Jiaqi Lu, Chunming Li, Xiafu Peng. Distance Measurement Based on Three-Dimensional Surface Reconstruction of Spatial Point Cloud[J]. Laser & Optoelectronics Progress, 2022, 59(14): 1415018 Copy Citation Text show less
    Three-dimensional reconstruction system based on binocular vision and line-structured light
    Fig. 1. Three-dimensional reconstruction system based on binocular vision and line-structured light
    Images captured by left and right cameras. (a) Image captured by left camera; (b) image captured by right camera
    Fig. 2. Images captured by left and right cameras. (a) Image captured by left camera; (b) image captured by right camera
    Line-structured light stripe extraction results. (a) Left camera extraction result; (b) right camera extraction result
    Fig. 3. Line-structured light stripe extraction results. (a) Left camera extraction result; (b) right camera extraction result
    Flow chart of point cloud acquisition
    Fig. 4. Flow chart of point cloud acquisition
    Difference between point cloud path of curved area and actual surface
    Fig. 5. Difference between point cloud path of curved area and actual surface
    Overall flow chart of geodesic algorithm
    Fig. 6. Overall flow chart of geodesic algorithm
    Differences in point cloud path search results between flat and curved areas
    Fig. 7. Differences in point cloud path search results between flat and curved areas
    Geodesic point cloud path search results. (a) Experiment 1; (b) experiment 2; (c) experiment 3; (d) experiment 4; (e) experiment 5; (f) experiment 6; (g) experiment 7; (h) experiment 8
    Fig. 8. Geodesic point cloud path search results. (a) Experiment 1; (b) experiment 2; (c) experiment 3; (d) experiment 4; (e) experiment 5; (f) experiment 6; (g) experiment 7; (h) experiment 8
    Geodesic point cloud path search results. (a) Experiment 1; (b) experiment 2; (c) experiment 3; (d) experiment 4; (e) experiment 5; (f) experiment 6; (g) experiment 7; (h) experiment 8
    Fig. 9. Geodesic point cloud path search results. (a) Experiment 1; (b) experiment 2; (c) experiment 3; (d) experiment 4; (e) experiment 5; (f) experiment 6; (g) experiment 7; (h) experiment 8
    Surface reconstruction results. (a) Greedy projection triangulation result; (b) poisson reconstruction result
    Fig. 10. Surface reconstruction results. (a) Greedy projection triangulation result; (b) poisson reconstruction result
    NumberManual measurement /mmProposed algorithm (polyline distance) /mmRelative error /%
    1116.0116.8070.696
    2241.0241.8580.356
    3311.0312.7260.555
    4600.0599.3590.107
    5118.5118.7320.196
    6370.0372.3840.644
    7171.0171.5600.327
    8124.0123.7950.165
    Table 1. Statistical table of distance measurement results of edge paths and geodesic point cloud paths in flat areas
    NumberManual measurement /mmPolyline distance /mmRelative error /%Poisson reconstruction /mmRelative error /%Proposed algorithm /mmRelative error /%
    1127.0126.3110.543127.2110.166127.4150.327
    2246.0244.8600.463245.2250.315245.9890.004
    3360.0358.8470.320359.0580.262359.5910.114
    4389.0388.9040.025388.9980.001389.2120.054
    5463.0460.0170.644461.8320.252462.5040.107
    6547.0544.1900.514545.6530.246546.4830.095
    7610.5607.0800.560607.3990.508607.6850.461
    8618.0617.8620.022617.9130.014617.8910.018
    Table 2. Statistical table of geodesic point cloud path measurement results
    Dongyun Lin, Jiaqi Lu, Chunming Li, Xiafu Peng. Distance Measurement Based on Three-Dimensional Surface Reconstruction of Spatial Point Cloud[J]. Laser & Optoelectronics Progress, 2022, 59(14): 1415018
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