• Laser & Optoelectronics Progress
  • Vol. 62, Issue 2, 0215006 (2025)
Zichao Chen1,2,*, Wen Ren2,3, and Long Wu2,3
Author Affiliations
  • 1School of Mechanical and Electronic Engineering, Fujian Agriculture and Forestry University,Fuzhou 350002, Fujian , China
  • 2Key Laboratory of Equipment Intelligence Control of Fujian Province, Sanming University,Sanming 365004, Fujian China
  • 3College of Mechanical and Electrical Engineering, Sanming University, Sanming 365004, Fujian , China
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    DOI: 10.3788/LOP241190 Cite this Article Set citation alerts
    Zichao Chen, Wen Ren, Long Wu. KD-Tree-Guided Surface-Curvature-Driven SteelBillet Point-Cloud Simplification Algorithm[J]. Laser & Optoelectronics Progress, 2025, 62(2): 0215006 Copy Citation Text show less
    KDSCP algorithm flow
    Fig. 1. KDSCP algorithm flow
    Three-dimensional space KD-tree segmentation diagram
    Fig. 2. Three-dimensional space KD-tree segmentation diagram
    KD-tree partition plan
    Fig. 3. KD-tree partition plan
    k-nearest neighbor search example
    Fig. 4. k-nearest neighbor search example
    Centroid nearest neighbor point simplification method
    Fig. 5. Centroid nearest neighbor point simplification method
    Collection field of point cloud data for steel billets
    Fig. 6. Collection field of point cloud data for steel billets
    Schematic diagram of structured light scanner data acquisition
    Fig. 7. Schematic diagram of structured light scanner data acquisition
    Simplification results and packaging model of KDSCP. (a) (h) Original point cloud encapsulation model; (b)(i) simplify 55.56%; (c)(j) simplify 65.44%; (d)(k) simplify 75.31%; (e)(l) simplify 85.19%
    Fig. 8. Simplification results and packaging model of KDSCP. (a) (h) Original point cloud encapsulation model; (b)(i) simplify 55.56%; (c)(j) simplify 65.44%; (d)(k) simplify 75.31%; (e)(l) simplify 85.19%
    Simplification results and packaging model of random sampling method. (a)(h) Original point cloud encapsulation model; (b)(i) simplify 55.56%; (c)(j) simplify 65.44%; (d)(k) simplify 75.31%; (e)(l) simplify 85.19%
    Fig. 9. Simplification results and packaging model of random sampling method. (a)(h) Original point cloud encapsulation model; (b)(i) simplify 55.56%; (c)(j) simplify 65.44%; (d)(k) simplify 75.31%; (e)(l) simplify 85.19%
    Simplification results and packaging model of Improved curvature sampling method. (a)(h) Original point cloud encapsulation model; (b) (i) simplify 55.62%; (c)(j) simplify 65.95%; (d) (k) simplify 75.26%; (e) (l) simplify 85.19%
    Fig. 10. Simplification results and packaging model of Improved curvature sampling method. (a)(h) Original point cloud encapsulation model; (b) (i) simplify 55.62%; (c)(j) simplify 65.95%; (d) (k) simplify 75.26%; (e) (l) simplify 85.19%
    Turbine 3D model
    Fig. 11. Turbine 3D model
    KDSCP-based encapsulated turbine model. (a) Original turbine model; (b) simplify 54.75%; (c) simplify 64.77%; (d) simplify 75.43%; (e) simplify 85.45%
    Fig. 12. KDSCP-based encapsulated turbine model. (a) Original turbine model; (b) simplify 54.75%; (c) simplify 64.77%; (d) simplify 75.43%; (e) simplify 85.45%
    Random sampling method-based encapsulated turbine model. (a) Original turbine model; (b) simplify 54.75%; (c) simplify 64.77%; (d) simplify 75.43%; (e) simplify 85.45%
    Fig. 13. Random sampling method-based encapsulated turbine model. (a) Original turbine model; (b) simplify 54.75%; (c) simplify 64.77%; (d) simplify 75.43%; (e) simplify 85.45%
    Improved curvature sampling method-based encapsulated turbine model. (a) Original turbine model; (b) simplify 54.77%; (c) simplify 65.14%; (d) simplify 75.42%; (e) simplify 85.61%
    Fig. 14. Improved curvature sampling method-based encapsulated turbine model. (a) Original turbine model; (b) simplify 54.77%; (c) simplify 65.14%; (d) simplify 75.42%; (e) simplify 85.61%
    Key feature areas of steel billet point cloud
    Fig. 15. Key feature areas of steel billet point cloud
    Comparison of key feature retention rates of three methods under different simplification rates
    Fig. 16. Comparison of key feature retention rates of three methods under different simplification rates
    Comparison of PSNR for steel billet simplification results using three methods under different reduction rates
    Fig. 17. Comparison of PSNR for steel billet simplification results using three methods under different reduction rates
    Comparison of point cloud information entropy in simplified results of steel billet
    Fig. 18. Comparison of point cloud information entropy in simplified results of steel billet
    Comparison of point cloud information entropy in simplified results of turbine
    Fig. 19. Comparison of point cloud information entropy in simplified results of turbine
    Simplification rate /%Hausdorff distance /mm
    55657585
    Random sampling method20.083720.217422.218323.2245
    Improved curvature sampling method18.758619.452319.995822.1912
    KDSCP16.204617.450718.176320.3291
    Table 1. Comparison of hausdorff distance for simplification results of three methods