Rapid Calibration Method for 3D Laser Scanner

Author(s): Bin Liu, Qian Qiao, Fangfang Han*

Journal Name: Recent Patents on Engineering

Volume 14 , Issue 2 , 2020


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Graphical Abstract:


Abstract:

Background: The 3D laser scanner is a non-contact active-sensing system, which has a number of applications. Many patents have been filed on the technologies for calibrating 3D laser scanner. A precise calibration method is important for measuring the accuracy of the 3D laser scanner. The system model contains three categories of parameters to be calibrated which include the camera intrinsic parameters, distortion coefficients and the light plane parameters. Typically, the calibration process is completed in two steps. Based on Zhang’s method, the calibration of the camera intrinsic parameters and distortion coefficients can be performed. Then, 3D feature points on the light plane should precisely be formed and extracted. Finally, the points are used to calculate the light plane parameters.

Methods: In this paper, a rapid calibration method is presented. Without any high precision auxiliary device, only one coplanar reference target is used. By using a group of captured images of the coplanar reference target placed in the field of view arbitrarily, calibration can be performed in one step. Based on the constraint from the planes formed by the target in different directions and the camera imaging model, a large amount of 3D points on the light plane can easily be obtained. The light plane equation in the camera coordinates system can be gathered by executing plane fitting to the 3D points.

Results: During the experimental process, the developed 3D laser scanner was calibrated by the proposed method. Then, the measuring accuracy of the system was verified with known distance in vertical direction of 1mm with sequential shifting motion generated by precision translation stage. The average value of the measured distances was found to be 1.010mm. The standard deviation was 0.008mm.

Conclusion: Experimental results prove that the proposed calibration method is simple and reliable.

Keywords: 3D laser scanner, structured light, calibration, coplanar target, system model, light plane.

[1]
W. Huang, and R. Kovacevic, "A laser-based vision system for weld quality inspection", Sensors (Basel), vol. 11, no. 1, pp. 506-521, 2011.
[http://dx.doi.org/10.3390/s110100506 ] [PMID: 22344308]
[2]
L. Maier-Hein, P. Mountney, A. Bartoli, H. Elhawary, D. Elson, A. Groch, A. Kolb, M. Rodrigues, J. Sorger, S. Speidel, and D. Stoyanov, "Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery", Med. Image Anal.. vol. 17, no. 8, pp. 974-996, 2013.,
[http://dx.doi.org//10.1016/j.media.2013.04.003] [PMID: 23837969]
[3]
K. Yatabe, K. Ishikawa, and Y. Oikawa, "Compensation of fringe distortion for phase-shifting three-dimensional shape measurement by inverse map estimation", Appl. Opt., vol. 55, no. 22, pp. 6017-6024, 2016.
[http://dx.doi.org/10.1364/AO.55.006017 ] [PMID: 27505383]
[4]
J.S. Ahn, A. Park, J.W. Kim, B.H. Lee, and J.B. Eom, "Development of three-dimensional dental scanning apparatus using structured illumination", Sensors (Basel), vol. 17, no. 7, p. 1634, 2017.
[http://dx.doi.org/10.3390/s17071634 ] [PMID: 28714897]
[5]
S. Logozzo, M. Valigi, and G. Canella, Advances in optomechatronics: an automated tilt-rotational 3D scanner for high-quality reconstructionsPhotonics,. vol. 5. 2018, no. 4, p. 42.,
[http://dx.doi.org/10.3390/photonics5040042]
[6]
M. Pallone, P.M. Meaney, and K.D. Paulsen, 3D scanning laser systems and methods for determining surface geometry of an immersed object in a transparent cylindrical glass tank.U.S. Patent 9,532,029 B2, December 27, 2016,
[7]
S.M. Edmonds, and S.P. Kearney, Hybrid-type bioptical laser scanning and digital imaging system supporting automatic object motion detection at the edges of a 3D scanning volume. U.S. Patent 8,998,091 B2, April 7, 2015,
[8]
T.S. Goodman, W.B. Buel, V. Anantha, and R.J. Steiner, Laser scanning systems and methods. U.S. Patent 9.418,424 B2 August 16, 2016.,
[9]
A. Shpunt, B. Pesach, and R. Akerman, Scanning projectors and image capture modules for 3D mapping.U.S. Patent 2017/0244955 A1, August 24, 2015,
[10]
T-H. Lin, Method and system for calibrating laser measuring apparatus. U.S. Patent 9.275.431 B2, March 1, 2016,
[11]
J. Small, K. Gross, and V.P. Errico, Method of processing calibration data in 3D laser scanner systems.U.S. Patent 10,295,820 B2, May 21, 2019,
[12]
S. Coeck, and K. Renap, System and method for calibrating a laser scanning system.U.S. Patent 9,993,976 B2, June 12, 2018.,
[13]
Q. Huang, "Systems and methods for predicting and improving scanning geometric accuracy for 3d scanners", U.S. Patent 2016/0299996 A1, October13, 2016.,
[14]
P. Kiddee, Z. Fang, and M. Tan, "A practical and intuitive calibration technique for cross-line structured light", Optik (Stuttg.), vol. 127, no. 20, pp. 9582-9602, 2016.
[http://dx.doi.org/10.1016/j.ijleo.2016.06.098]
[15]
J. Xu, J. Douet, J. Zhao, L. Song, and K. Chen, "A simple calibration method for structured light-based 3D profile measurement", Opt. Laser Technol., vol. 48, pp. 187-193, 2013.
[http://dx.doi.org/10.1016/j.optlastec.2012.09.035]
[16]
Z. Wei, L. Cao, and G. Zhang, "A novel 1D target-based calibration method with unknown orientation for structured light vision sensor", Opt. Laser Technol., vol. 42, no. 4, pp. 570-574, 2010.
[http://dx.doi.org/10.1016/j.optlastec.2009.10.005]
[17]
G. Zhang, Z. Liu, J. Sun, and Z. Wei, "Novel calibration method for a multi-sensor visual measurement system based on structured light", Opt. Eng.,. vol. 49, no. 4, 2010.043602,
[http://dx.doi.org/10.1117/1.3407429]
[18]
Z. Zhang, "A flexible new technique for camera calibration.in", IEEE Transactions on. Pattern Analysis and. Machine. Intelligence,.vol. 22, no. 11, pp. 1330-1334, Nov. 2000,
[http://dx.doi.org/10.1109/34.888718]
[19]
Z. Zhang, "Flexible camera calibration by viewing a plane from unknown orientations,"In Proceedings of the Seventh IEEE International Conference on Computer Vision, Kerkyra, Greece, 1999, pp. 666-673 vol.1.,
[http://dx.doi.org/10.1109/ICCV.1999.791289]
[20]
R. Dewar, "Self-generated targets for spatial calibration of structured-light optical sectioning sensors with respect to an external coordinate system presented", In Conference Robots 12 and Vision ’88.Detroit, Michigan June 6-9, 1988.,
[21]
F. Duan, F. Liu, and S. Ye, "A New Accurate Method for the Calibration of Line Structured Light Sensor", Yiqi Yibiao Xuebao, vol. 21, no. 1, pp. 108-110, 2000.
[22]
D.Q. Huynh, R.A. Owens, and P.E. Hartmann, "Calibrating a structured light stripe system: a novel approach", Int. J. Comput. Vision, vol. 33, no. 1, pp. 73-86, 1999.
[http://dx.doi.org/10.1023/A:1008117315311]
[23]
Y. Zou, M. Zhao, and L. Zhang, "Direct calibration method of laser stripe vision sensor based on gauge block", Chin. J. Lasers,.vol. 41, no. 11, 2014.1108002,
[http://dx.doi.org/10.3788/CJL201441.1108002]
[24]
Z. Liu, X. Li, F. Li, and G. Zhang, "Calibration method for line-structured light vision sensor based on a single ball target", Opt. Lasers Eng., vol. 69, pp. 20-28, 2015.
[http://dx.doi.org/10.1016/j.optlaseng.2015.01.008]
[25]
L. Tao, C. Sun, and L. He, "Y. ZHANG, and S. YE, “A color 3-D acquisition method based on structured-light scanning", J. Optoelectron Laser, vol. 17, no. 1, pp. 111-114, 2006.
[26]
G. Zhang, Z. Wei, Z. Sun, and X. Li, "A method of structured light based 3D vision inspection using BP neural network", Yiqi Yibiao Xuebao, vol. 23, no. 1, pp. 31-35, 2002.
[27]
J. Zhu, Y. Li, and S. Ye, "A speedy method for the calibration of line structured light sensor based on coplanar reference target", Chin. Mech. Eng., vol. 17, no. 2, pp. 183-186, 2006.


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Article Details

VOLUME: 14
ISSUE: 2
Year: 2020
Published on: 28 October, 2020
Page: [234 - 241]
Pages: 8
DOI: 10.2174/1872212113666191016140122
Price: $25

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