Abstract
In this paper, a flexible high-precision calibration method suitable for industrial field was proposed. The complexity of the coordinate transformation was simplified by choosing the camera coordinate system as the unified reference coordinate system. A flexible planar calibration pattern was introduced to the calibration process, which can be arbitrarily placed and from which the known feature points can be extracted to construct other unknown feature points. With the known intrinsic parameters, the laser projector plane equation was fitted by the multi-noncollinear points, which were acquired through the principle of triangulation and the projective invariance of cross ratio. With this method, the strict alignment and multiple times of coordinate transformation can be avoided. Experimental results showed that the arithmetic mean of the root mean square (RMS) error of distance was 0.000 7 mm.
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References
Blais F. Review of 20 years of range sensor development[ J]. Journal of Electronic Imaging, 2004, 13(1): 231–243.
Srinivasan V, Liu H C, Halioua M. Automated phasemeasuring profilometry of 3-D diffuse objects[J]. Applied Optics, 1984, 23(18): 3105–3108.
Skydan O A, Lalor M J, Burton D R. Three-dimensional shape measurement of non-full-field reflective surfaces[J]. Applied Optics, 2005, 44(22): 4745–4752.
Li W, Bothe T, von Kopylow C et al. Evaluation methods for gradient measurement techniques[C]. In: Proceedings of the SPIE on Optical Metrology in Production Engineering. Strasbourg, France, 2004.
Tsai R Y. A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-theshelf TV cameras and lenses[J]. IEEE Journal of Robotics and Automation, 1987, 3(4): 323–344.
Ma S D, Zhang Z Y. Computer Vision. Computational Theory and Algorithm[M]. Science Press, Beijing, China, 1998 (in Chinese).
Ma S D, Zhang Z Y. Computer Vision[M]. Science Press, Beijing, China, 1998 (in Chinese).
Abdel-Aziz Y I, Karara H M. Direct linear transformation from comparator coordinates into object space coordinates in close-range photogrammetry[C]. In: Proceedings of the Symposium on Close-Range Photogrammetry. Urbana, Illinois, USA, 1971.
Zhang Zhengyou. Camera calibration with onedimensional objects[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(7): 892–899.
Zhang Z. Flexible camera calibration by viewing a plane from unknown orientations[C]. In: Proceedings of the Seventh IEEE International Conference on Computer Vision. Corfu, Greece, 1999.
Hartley Richard I. Estimation of relative camera positions for uncalibrated cameras[C]. In: Proceedings of the 2nd European Conference on Computer Vision. Santa Margherita Ligure, Italy, 1992.
Maybank Stephen J, Faugeras Olivier D. A theory of selfcalibration of a moving camera[J]. International Journal of Computer Vision, 1992, 8(2): 123–151.
Luong Q T, Faugeras O D. Self-calibration of a moving camera from point correspondences and fundamental matrices[J]. International Journal of Computer Vision, 1997, 22(3): 261–289.
Cyril Zeller, Olivier Faugeras. Camera Self-Calibration from Video Sequences: The Kruppa Equations Revisited[R]. Research Report 2793. INRIA, France, 1996.
Xu Gang, Sugimoto Noriko. Algebraic derivation of the Kruppa equations and a new algorithm for self-calibration of cameras[J]. Journal of Optical Society of America A, 1999, 16(10): 2419–2424.
Dewar R. Self-generated targets for spatial calibration of structured-light optical sectioning sensors with respect to an external coordinate system[C]. In: Proceedings on Robots and Vision’ 88 Conference. Detroit, USA, 1988.
Duan Fajie, Liu Fengmei, Ye Shenghua. A new accurate method for the calibration of line structured light sensor[ J]. Chinese Journal of Scientific Instrument, 2000, 21(1): 108–110(in Chinese).
Xu Guangyou, Liu Lifeng, Zeng Jianchao et al. A new method of calibration in 3D vision system based on structure- light[J]. Chinese Journal of Computers, 1995, 18(6): 450–456(in Chinese).
Liu Yan, Wang Qinglin, Li Yuan et al. A calibration method for a linear structured light system with three collinear points[J]. International Journal of Computational Intelligence Systems, 2011, 4(6): 1298–1306.
Zhang Guangjun, He Junji, Yang Xianming. Calibrating camera radial distortion with cross-ratio invariability[J]. Optics and Laser Technology, 2003, 35(6): 457–461.
Zhou Fuqiang, Zhang Guangjun. Complete calibration of a structured light stripe vision sensor through planar target of unknown orientations[J]. Image and Vision Computing, 2005, 23(1): 59–67.
Sun Changku, Zhang Xiaodong, Chen Shan. Method of Determining Target Topological Relations and Flexible Camera Calibration Pattern: China, ZL200610014481[P]. 2008-01-02(in Chinese).
Zhang Xiaodong, Sun Changku. Novel directional pattern and mapping location algorithm[J]. Computer Engineering and Applications, 2008, 44(11): 104–106(in Chinese).
Fang Dezhi, Chen Yipei. Projective Geometry[M]. Higher Education Press, Beijing, China, 1983(in Chinese).
Wu Fuchao, Wang Guanghui, Hu Zhanyi. A linear approach for determining intrinsic parameters and pose of cameras from rectangles[J]. Journal of Software, 2003, 14(3): 703–712.
Moré J J. The Levenberg-Marquardt Algorithm: Implementation and Theory. Numerical Analysis[M]. Springer-Verlag, Berlin, Germany, 1977.
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Supported by the National Natural Science Foundation of China (No. 51105273).
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Yang, Z., Wang, P., Li, X. et al. Flexible calibration method for 3D laser scanner system. Trans. Tianjin Univ. 20, 27–35 (2014). https://doi.org/10.1007/s12209-014-2167-0
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DOI: https://doi.org/10.1007/s12209-014-2167-0