Open Access
J. Eur. Opt. Soc.-Rapid Publ.
Volume 15, Number 1, 2019
Article Number 1
Number of page(s) 11
Published online 15 January 2019
  1. Chung BM, Improved least-squares method for phase-to-height relationship in fringe projection profilometry (2016) [Google Scholar]
  2. Dewar R, Self-generated targets for spatial calibration of structured light optical sectioning sensors with respect to an external coordinate system. Proceedings of the Robots and Vision Conference (1988) USADetroit, Mich5–13. [Google Scholar]
  3. James KW, “Noncontact machine vision metrology with a CAD coordinate system,” Autofact’88 Conference Proceedings (1988) 9–17. [Google Scholar]
  4. Duan F, Liu F, Ye S, A new accurate method for the calibration of line structured light sensor. Chinese Journal of Scientific Instrument (2000) 211, 108–110. [Google Scholar]
  5. Xu G, Liu L, Zeng J, A new method of calibration in 3D vision system based on structure-light. Chinese Journal of Computers (1995) 18, 6450–456. [Google Scholar]
  6. Huynh DQ, Owens RA, Hartmann PE, Calibrating a structured light stripe system: a novel approach. Int. J. Comput. Vis. (1999) 33, 173–86. [CrossRef] [Google Scholar]
  7. Wei Z, Zhang G, Xu Y, Calibration approach for structured-light-stripe vision sensor based on the invariance of double cross-ratio. Opt. Eng. (2003) 42, 102956–2966. [CrossRef] [Google Scholar]
  8. Wei Z, Cao L, Zhang G, A novel 1D target-based calibration method with unknown orientation for structured light vision sensor. Opt. Laser Technol. (2010) 42, 4570–574. [NASA ADS] [CrossRef] [Google Scholar]
  9. Zhou F, Cai F, Calibrating structured-light vision sensor with one-dimensional target. Journal of Mechanical Engineering (2010) 46, 187–12. [CrossRef] [Google Scholar]
  10. Zhou F, Zhang G, Complete calibration of a structured light stripe vision sensor through planar target of unknown orientations. Image Vis. Comput. (2005) 23, 159–67. [CrossRef] [Google Scholar]
  11. Wei Z, Xie M, Zhang G, “Calibration method for line structured light vision sensor based on vanish points and lines”, ICPR (2010) 794–797. [Google Scholar]
  12. Xu, K.: Monolithically integrated Si Gate-controlled light-emitting device: science and properties. Journal of Optics. 024014: [Google Scholar]
  13. Harun SW, Lim KS, Damanhuri SSA, Ahmad H, Microfiber loop resonator based temperature sensor (2011) [Google Scholar]
  14. Huang H, Zhang H, Cheung Y, “The common self-polar triangle of concentric circles and its application to camera calibration”, IEEE Conference on Computer Vision and Pattern Recognition (2015) 4065–4072. [Google Scholar]
  15. Mao, J., Huang, X., Jiang, L.: “A flexible solution to AX=XB for Robot Hand-Eye calibration”, 10th WSEAS Int. In: Conference on ROBOTICS, CONTROL and MANUFACTURING TECHNOLOGY, pp. 118–122 [Google Scholar]
  16. Shiu Y, Ahmad S, 3D location of circular spherical features by monocular model-based vision. Proceedings of the IEEE Conference on System, Man and Cybernetics (1989) USACambridge, Mass576–581. [CrossRef] [Google Scholar]
  17. Safaee-Rad R, Tchoukanov I, Smith KC, Benhabib B, Three-dimensional location estimation of circular features for machine vision. IEEE Trans. Robot. Autom. (1992) 8, 5624–640. [CrossRef] [Google Scholar]
  18. R. Hartley and A. Zisserman, “Multiple View Geometry in Computer Vision”, Cambridge University Press, 2003, ch.2–8 [Google Scholar]
  19. Zhang Z, A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. (2000) 22, 111330–1334. [CrossRef] [Google Scholar]
  20. J. Bouguet, “Camera calibration toolbox for Matlab”, [Online] Available from: [Google Scholar]
  21. Steger C, Unbiased extraction of curvilinear structures from 2D and 3D image [Ph.D. Dissertation], Technische Universitaet Muenchen (1998) [Google Scholar]

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