A multi-line laser scanning system design and evaluation framework based on physical simulation

Abstract

We propose a multi-line laser simulation system utilizing computer graphics and physical simulation to generate virtual multi-line laser datasets. Our framework provides key physical properties of the scene, including camera parameters, depth values, surface normals, and the actual two-dimensional (2D) and three-dimensional (3D) coordinates of the laser stripe centers for each rendered image. Beyond, we construct a virtual line laser scanning image dataset with a complex background by simulating interactions between lasers and object surfaces with the Monte Carlo method. With the proposed framework and dataset, a multi-line laser extraction algorithm based on a robust sorting algorithm is proposed and tested, which utilizes distance-based error analysis, connected component labeling, and iterative optimization refinement techniques. Both simulation and actual experiments show that our method outperforms the other state-of-the-art multi-line laser stripe center extraction methods. The proposed framework can be applied to different types of laser scanning systems in the future.

Keywords

A

References

[1] Ye C, Feng W, Wang Q, et al.. Laser stripe segmentation and centerline extraction based on 3D scanning imaging. Applied optics, 2022, 61(18): 5409-5418 J]

[2] Wang S H, Qiao Z F, Huang J, et al.. A calibration method of external parameters of 2D laser in rotary 3D scanning. Optoelectronics letters, 2022, 18(12): 730-736 J]

[3] Chen Y, Li Y, Niu G, et al.. Offline and online measurement of the geometries of train wheelsets: a review. IEEE transactions on instrumentation and measurement, 2022, 71: 1-15[J]

[4] Jia X, Yang S R, Guan D Y. Semantics-aware transformer for 3D reconstruction from binocular images. Optoelectronics letters, 2022, 18(5): 293-299 J]

[5] Song L M, He J S, Li Y P. Center extraction method for reflected metallic surface fringes based on line structured light. Journal of the Optical Society of America A, 2024, 41(3): 550-559 J]

[6] Zhao H Y, Liu X, Wang S, et al.. An enhanced centerline extraction algorithm for complex stripes in linear laser scanning measurement. Precision engineering, 2024, 91: 199-211 J]

[7] Liu H, Liu Y N, Zhang X Y. Research on dynamic measurement method of speckle in laser display. Optoelectronics letters, 2024, 20(6): 360-366 J]

[8] Feng S Q, Li Q, Huang J X, et al.. Posture planning method for complex feature measurement using a single-line laser scanner. Applied optics, 2023, 62(36): 9544-9552 J]

[9] Wu F, Mao J, Zhou Y F. Three-line structured light measurement system and its application in ball diameter measurement. Optik, 2018, 157: 222-229 J]

[10] Lilienblum E, Al-Hamadi A. A structured light approach for 3-D surface reconstruction with a stereo line-scan system. IEEE transactions on instrumentation and measurement, 2015, 64(5): 1258-1266 J]

[11] Zhang J, Sun J H, Zhang Z. Identifying multiple line-structured lights from images via a local-to-global graph representation. Optics express, 2020, 28(10): 15611-15624 J]

[12] Xue J, Hu Y, Li G, et al.. A novel and robust method of indexing the uncoded stripes for multi-line based structured light application. Electronics letters, 2021, 57(25): 967-969 J]

[13] Li W G, Deng H B, Deng Z P, et al.. Multi-line structured light stripes clustering based on a custom iterative window. Heliyon, 2024, 10(15): 35437-35484 J]

[14] Liu Y W, Sun J H, Zhou F Q, et al.. Identifying the laser stripes via ray model for multiline structured light stereo vision sensors. IEEE sensors journal, 2024, 24(21): 34808-34815 J]

[15] Sun Q C, Ren Z M, Zhu J L, et al.. A three-dimensional structured light vision system by using a combination of single-line and three-line lasers. Sensors, 2022, 23(1): 13 J]

[16] Deng L, Liu G H, Huang H M, et al.. Binocular multi-line laser segment stereo matching based on projective geometric constraints and scoring mechanism. Measurement, 2025, 245: 116596-116608 J]

[17] Wan M S, Zheng R H, Wang S D, et al.. Efficient 3D scanning measurement system based on asymmetric trinocular vision and a multi-line laser. Applied optics, 2023, 62(8): 2145-2153 J]

[18] Li W G, Luo Z X, Hou D M, et al.. Multi-line laser projection 3D measurement simulation system technology. Optik, 2021, 231: 166390-166404 J]

[19] Puljcan A, Zoraja D, Petkovc T. Simulation of structured light 3D scanning using Blender. 2022 International Symposium ELMAR, September 12–14, 2022, Zadar, Croaria, 2022New YorkIEEE215-220[C]

[20] Paulin G, Marina I K. Review and analysis of synthetic dataset generation methods and techniques for application in computer vision. Artificial intelligence review, 2023, 56(9): 9221-9265 J]

[21] Cartucho J, Tukra S, Li Y, et al.. VisionBlender: a tool to efficiently generate computer vision datasets for robotic surgery. Computer methods in biomechanics and biomedical engineering: imaging & visualization, 2021, 9(4): 331-338[J]

RIGHTS & PERMISSIONS

Tianjin University of Technology