Distance Measurement Based on Three-Dimensional Surface Reconstruction of Spatial Point Cloud

Dongyun Lin; Jiaqi Lu; Chunming Li; Xiafu Peng

doi:10.3788/LOP202259.1415018

Laser & Optoelectronics Progress, Volume. 59, Issue 14, 1415018(2022)

Distance Measurement Based on Three-Dimensional Surface Reconstruction of Spatial Point Cloud

Dongyun Lin¹, Jiaqi Lu¹, Chunming Li^2、*, 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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Figures & Tables(12)

Fig. 1. Three-dimensional reconstruction system based on binocular vision and line-structured light

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Fig. 2. Images captured by left and right cameras. (a) Image captured by left camera; (b) image captured by right camera

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Fig. 3. Line-structured light stripe extraction results. (a) Left camera extraction result; (b) right camera extraction result

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Fig. 4. Flow chart of point cloud acquisition

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Fig. 5. Difference between point cloud path of curved area and actual surface

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Fig. 6. Overall flow chart of geodesic algorithm

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Fig. 7. Differences in point cloud path search results between flat and curved areas

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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

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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

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Fig. 10. Surface reconstruction results. (a) Greedy projection triangulation result; (b) poisson reconstruction result

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Table 1. Statistical table of distance measurement results of edge paths and geodesic point cloud paths in flat areas

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Table 1. Statistical table of distance measurement results of edge paths and geodesic point cloud paths in flat areas

Number	Manual measurement /mm	Proposed algorithm （polyline distance） /mm	Relative error /%
1	116.0	116.807	0.696
2	241.0	241.858	0.356
3	311.0	312.726	0.555
4	600.0	599.359	0.107
5	118.5	118.732	0.196
6	370.0	372.384	0.644
7	171.0	171.560	0.327
8	124.0	123.795	0.165

Table 2. Statistical table of geodesic point cloud path measurement results

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Table 2. Statistical table of geodesic point cloud path measurement results

Number	Manual measurement /mm	Polyline distance /mm	Relative error /%	Poisson reconstruction /mm	Relative error /%	Proposed algorithm /mm	Relative error /%
1	127.0	126.311	0.543	127.211	0.166	127.415	0.327
2	246.0	244.860	0.463	245.225	0.315	245.989	0.004
3	360.0	358.847	0.320	359.058	0.262	359.591	0.114
4	389.0	388.904	0.025	388.998	0.001	389.212	0.054
5	463.0	460.017	0.644	461.832	0.252	462.504	0.107
6	547.0	544.190	0.514	545.653	0.246	546.483	0.095
7	610.5	607.080	0.560	607.399	0.508	607.685	0.461
8	618.0	617.862	0.022	617.913	0.014	617.891	0.018

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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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Paper Information

Category: Machine Vision

Received: May. 6, 2022

Accepted: Jun. 21, 2022

Published Online: Jul. 18, 2022

The Author Email: Chunming Li (chunming.li@uestc.edu.cn)

DOI:10.3788/LOP202259.1415018

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology