Abstract

Previous stereo-vision based methods for measuring bent tube axis usually approximate the centerlines of image contours as the axis projection, inevitably resulting in reconstruction errors. This phenomenon is more significant as the tube diameter increases. In this paper, a perspective projection model for any cross section of bent tube was established. Based on this model, a way to locate the precise projected position on image planes of points laying on axis was proposed and 3D coordinates of axis points are reconstructed by binocular stereo vision. We measured three bent tubes with different diameters. Compared with classical approaches, this method effectively reduces the reconstruction errors with measurement accuracy practically independent of diameter.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Full Article  |  PDF Article
OSA Recommended Articles
3D pose estimation of large and complicated workpieces based on binocular stereo vision

Zhifeng Luo, Ke Zhang, Zhigang Wang, Jian Zheng, and Yixin Chen
Appl. Opt. 56(24) 6822-6836 (2017)

Omnidirectional stereo vision sensor based on single camera and catoptric system

Fuqiang Zhou, Xinghua Chai, Xin Chen, and Ya Song
Appl. Opt. 55(25) 6813-6820 (2016)

Automated stereo vision instrument tracking for intraoperative OCT guided anterior segment ophthalmic surgical maneuvers

Mohamed T. El-Haddad and Yuankai K. Tao
Biomed. Opt. Express 6(8) 3014-3031 (2015)

References

  • View by:
  • |
  • |
  • |

  1. X. Ji and G. Gong, “Study of Realization Technologies for 3D Reconstruction of Superchargers′ Impellers,” J. Mech. Sci. Technol. 25(3), 322–325 (2006).
  2. Y. Wei and A. Thornton, “Tube production and assembly systems: the impact of compliance and variability on yield,” presented at Design Engineering Technical Conferences and Computer and Information in Engineering Conference, Baltimore, Maryland, 10–13 Sept. (2000).
  3. Extreme Networks white paper, “Virtual metropolitan area networks,” (Extreme Networks, 2001), http://www.extremenetworks.com/technology/whitepapers/vMAN.asp .
  4. F. Gu, H. Zhao, X. Zhou, J. Li, P. Bu, and Z. Zhao, “Photometric invariant stereo matching method,” Opt. Express 23(25), 31779–31792 (2015).
    [Crossref] [PubMed]
  5. Z. Liu, X. Li, F. Li, and G. Zhang, “Flexible dynamic measurement method of three-dimensional surface profilometry based on multiple vision sensors,” Opt. Express 23(1), 384–400 (2015).
    [Crossref] [PubMed]
  6. A. S. Metronor, Homepage, “Metronor One,” (Metronor, 2011–2018), http://www.metronor.com .
  7. Gesellschaft für optische Messtechnik mbH Homepage, “ATOS Core – Optical 3D Scanner,” (GOM, 2011–2018), https:// www.gom.com/metrology-systems/atos/atos-core.html .
  8. W. Bösemann, “Industrial photogrammetry-accepted METROLOGY tool or exotic niche,” presented at the International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, Prague, Czech Republic,12–19 July. (2016).
  9. AICON 3D Systems GmbH Homepage, “Aicon-scanner,” (AICON, 2011–2018), https://www.aicon3d.com/de-DE/products/aicon-scanner .
  10. AICON 3D Systems GmbH Homepage, “Tubeinspect,”(AICON, 2011–2018), https://www.aicon3d.com/de-DE/products/tubeinspect .
  11. P. Jin, J. Liu, S. Liu, and X. Wang, “Automatic multi-stereo-vision reconstruction method of complicated tubes for industrial assembly,” Assem. Autom. 36(4), 362–375 (2016).
    [Crossref]
  12. S. Liu, J. Liu, P. Jin, and X. Wang, “Tube measurement based on stereo-vision: a review,” Int. J. Adv. Manuf. Technol. 92(5-8), 2017–2032 (2017).
    [Crossref]
  13. T. Zhang, J. Liu, S. Liu, C. Tang, and P. Jin, “A 3D reconstruction method for pipeline inspection based on multi-vision,” Measurement 98, 35–48 (2017).
    [Crossref]
  14. T. Zhang, J. Liu, C. Tang, and S. Liu, “3D reconstruction method of bent tube with NURBS curve,” in 2nd International Conference on Mechatronics and Applied Mechanics (ICMAM2012), C.K. Wang and J.Guo, ed. (Applied Mechanics and Materials, 2013), pp. 112–118.
    [Crossref]
  15. S. Liu, P. Jin, J. Liu, X. Wang, and P. Sun, “Accurate measurement method for tube’s endpoints based on machine vision,” Chin. J. Mech. Eng. 30(1), 152–163 (2017).
    [Crossref]
  16. C. Doignon and M. de Mathelin, “A degenerate conic-based method for a direct fitting and 3-d pose of cylinders with a single perspective view,” in Proceedings of IEEE International Conference on Robotics and Automation, (IEEE, 2007), pp. 4220–4225.
    [Crossref]
  17. C. Liu and W. Hu, “Relative pose estimation for cylinder-shaped spacecrafts using single image,” in IEEE Transactions on Aerospace and Electronic Systems, (IEEE, 2014), pp. 3036–3056.
  18. K. Wong, P. Mendonça, and R. Cipolla, “Reconstruction of surfaces of revolution from single uncalibrated views,” Image Vis. Comput. 22(10), 829–836 (2004).
    [Crossref]
  19. W. Bösemann, “The optical tube measurement system OLM photogrammetric methods used for industrial automation and process control,” presented at International Archives of Photogrammetry and Remote Sensing, Part B5, Vienna (1996).
  20. I.-K. Lee, “Curve reconstruction from unorganized points,” Comput. Aided Geom. Des. 17(2), 161–177 (2000).
    [Crossref]
  21. I.-K. Lee and K.-J. Kim, “Shrinking: Another method for surface reconstruction,” in Geometric Modeling and Processing, 2004. Proceedings, (IEEE, 2004), pp. 259–266.
  22. Caglioti and A. Giusti, “Reconstruction of canal surfaces from single images under exact perspective,” in European Conference on Computer Vision, A. Prinz, ed. (Springer, 2006), pp. 289–300.

2017 (3)

S. Liu, J. Liu, P. Jin, and X. Wang, “Tube measurement based on stereo-vision: a review,” Int. J. Adv. Manuf. Technol. 92(5-8), 2017–2032 (2017).
[Crossref]

T. Zhang, J. Liu, S. Liu, C. Tang, and P. Jin, “A 3D reconstruction method for pipeline inspection based on multi-vision,” Measurement 98, 35–48 (2017).
[Crossref]

S. Liu, P. Jin, J. Liu, X. Wang, and P. Sun, “Accurate measurement method for tube’s endpoints based on machine vision,” Chin. J. Mech. Eng. 30(1), 152–163 (2017).
[Crossref]

2016 (1)

P. Jin, J. Liu, S. Liu, and X. Wang, “Automatic multi-stereo-vision reconstruction method of complicated tubes for industrial assembly,” Assem. Autom. 36(4), 362–375 (2016).
[Crossref]

2015 (2)

2006 (1)

X. Ji and G. Gong, “Study of Realization Technologies for 3D Reconstruction of Superchargers′ Impellers,” J. Mech. Sci. Technol. 25(3), 322–325 (2006).

2004 (1)

K. Wong, P. Mendonça, and R. Cipolla, “Reconstruction of surfaces of revolution from single uncalibrated views,” Image Vis. Comput. 22(10), 829–836 (2004).
[Crossref]

2000 (1)

I.-K. Lee, “Curve reconstruction from unorganized points,” Comput. Aided Geom. Des. 17(2), 161–177 (2000).
[Crossref]

Bu, P.

Cipolla, R.

K. Wong, P. Mendonça, and R. Cipolla, “Reconstruction of surfaces of revolution from single uncalibrated views,” Image Vis. Comput. 22(10), 829–836 (2004).
[Crossref]

de Mathelin, M.

C. Doignon and M. de Mathelin, “A degenerate conic-based method for a direct fitting and 3-d pose of cylinders with a single perspective view,” in Proceedings of IEEE International Conference on Robotics and Automation, (IEEE, 2007), pp. 4220–4225.
[Crossref]

Doignon, C.

C. Doignon and M. de Mathelin, “A degenerate conic-based method for a direct fitting and 3-d pose of cylinders with a single perspective view,” in Proceedings of IEEE International Conference on Robotics and Automation, (IEEE, 2007), pp. 4220–4225.
[Crossref]

Gong, G.

X. Ji and G. Gong, “Study of Realization Technologies for 3D Reconstruction of Superchargers′ Impellers,” J. Mech. Sci. Technol. 25(3), 322–325 (2006).

Gu, F.

Ji, X.

X. Ji and G. Gong, “Study of Realization Technologies for 3D Reconstruction of Superchargers′ Impellers,” J. Mech. Sci. Technol. 25(3), 322–325 (2006).

Jin, P.

S. Liu, P. Jin, J. Liu, X. Wang, and P. Sun, “Accurate measurement method for tube’s endpoints based on machine vision,” Chin. J. Mech. Eng. 30(1), 152–163 (2017).
[Crossref]

T. Zhang, J. Liu, S. Liu, C. Tang, and P. Jin, “A 3D reconstruction method for pipeline inspection based on multi-vision,” Measurement 98, 35–48 (2017).
[Crossref]

S. Liu, J. Liu, P. Jin, and X. Wang, “Tube measurement based on stereo-vision: a review,” Int. J. Adv. Manuf. Technol. 92(5-8), 2017–2032 (2017).
[Crossref]

P. Jin, J. Liu, S. Liu, and X. Wang, “Automatic multi-stereo-vision reconstruction method of complicated tubes for industrial assembly,” Assem. Autom. 36(4), 362–375 (2016).
[Crossref]

Lee, I.-K.

I.-K. Lee, “Curve reconstruction from unorganized points,” Comput. Aided Geom. Des. 17(2), 161–177 (2000).
[Crossref]

Li, F.

Li, J.

Li, X.

Liu, J.

S. Liu, J. Liu, P. Jin, and X. Wang, “Tube measurement based on stereo-vision: a review,” Int. J. Adv. Manuf. Technol. 92(5-8), 2017–2032 (2017).
[Crossref]

T. Zhang, J. Liu, S. Liu, C. Tang, and P. Jin, “A 3D reconstruction method for pipeline inspection based on multi-vision,” Measurement 98, 35–48 (2017).
[Crossref]

S. Liu, P. Jin, J. Liu, X. Wang, and P. Sun, “Accurate measurement method for tube’s endpoints based on machine vision,” Chin. J. Mech. Eng. 30(1), 152–163 (2017).
[Crossref]

P. Jin, J. Liu, S. Liu, and X. Wang, “Automatic multi-stereo-vision reconstruction method of complicated tubes for industrial assembly,” Assem. Autom. 36(4), 362–375 (2016).
[Crossref]

Liu, S.

S. Liu, J. Liu, P. Jin, and X. Wang, “Tube measurement based on stereo-vision: a review,” Int. J. Adv. Manuf. Technol. 92(5-8), 2017–2032 (2017).
[Crossref]

T. Zhang, J. Liu, S. Liu, C. Tang, and P. Jin, “A 3D reconstruction method for pipeline inspection based on multi-vision,” Measurement 98, 35–48 (2017).
[Crossref]

S. Liu, P. Jin, J. Liu, X. Wang, and P. Sun, “Accurate measurement method for tube’s endpoints based on machine vision,” Chin. J. Mech. Eng. 30(1), 152–163 (2017).
[Crossref]

P. Jin, J. Liu, S. Liu, and X. Wang, “Automatic multi-stereo-vision reconstruction method of complicated tubes for industrial assembly,” Assem. Autom. 36(4), 362–375 (2016).
[Crossref]

Liu, Z.

Mendonça, P.

K. Wong, P. Mendonça, and R. Cipolla, “Reconstruction of surfaces of revolution from single uncalibrated views,” Image Vis. Comput. 22(10), 829–836 (2004).
[Crossref]

Sun, P.

S. Liu, P. Jin, J. Liu, X. Wang, and P. Sun, “Accurate measurement method for tube’s endpoints based on machine vision,” Chin. J. Mech. Eng. 30(1), 152–163 (2017).
[Crossref]

Tang, C.

T. Zhang, J. Liu, S. Liu, C. Tang, and P. Jin, “A 3D reconstruction method for pipeline inspection based on multi-vision,” Measurement 98, 35–48 (2017).
[Crossref]

Wang, X.

S. Liu, P. Jin, J. Liu, X. Wang, and P. Sun, “Accurate measurement method for tube’s endpoints based on machine vision,” Chin. J. Mech. Eng. 30(1), 152–163 (2017).
[Crossref]

S. Liu, J. Liu, P. Jin, and X. Wang, “Tube measurement based on stereo-vision: a review,” Int. J. Adv. Manuf. Technol. 92(5-8), 2017–2032 (2017).
[Crossref]

P. Jin, J. Liu, S. Liu, and X. Wang, “Automatic multi-stereo-vision reconstruction method of complicated tubes for industrial assembly,” Assem. Autom. 36(4), 362–375 (2016).
[Crossref]

Wong, K.

K. Wong, P. Mendonça, and R. Cipolla, “Reconstruction of surfaces of revolution from single uncalibrated views,” Image Vis. Comput. 22(10), 829–836 (2004).
[Crossref]

Zhang, G.

Zhang, T.

T. Zhang, J. Liu, S. Liu, C. Tang, and P. Jin, “A 3D reconstruction method for pipeline inspection based on multi-vision,” Measurement 98, 35–48 (2017).
[Crossref]

Zhao, H.

Zhao, Z.

Zhou, X.

Assem. Autom. (1)

P. Jin, J. Liu, S. Liu, and X. Wang, “Automatic multi-stereo-vision reconstruction method of complicated tubes for industrial assembly,” Assem. Autom. 36(4), 362–375 (2016).
[Crossref]

Chin. J. Mech. Eng. (1)

S. Liu, P. Jin, J. Liu, X. Wang, and P. Sun, “Accurate measurement method for tube’s endpoints based on machine vision,” Chin. J. Mech. Eng. 30(1), 152–163 (2017).
[Crossref]

Comput. Aided Geom. Des. (1)

I.-K. Lee, “Curve reconstruction from unorganized points,” Comput. Aided Geom. Des. 17(2), 161–177 (2000).
[Crossref]

Image Vis. Comput. (1)

K. Wong, P. Mendonça, and R. Cipolla, “Reconstruction of surfaces of revolution from single uncalibrated views,” Image Vis. Comput. 22(10), 829–836 (2004).
[Crossref]

Int. J. Adv. Manuf. Technol. (1)

S. Liu, J. Liu, P. Jin, and X. Wang, “Tube measurement based on stereo-vision: a review,” Int. J. Adv. Manuf. Technol. 92(5-8), 2017–2032 (2017).
[Crossref]

J. Mech. Sci. Technol. (1)

X. Ji and G. Gong, “Study of Realization Technologies for 3D Reconstruction of Superchargers′ Impellers,” J. Mech. Sci. Technol. 25(3), 322–325 (2006).

Measurement (1)

T. Zhang, J. Liu, S. Liu, C. Tang, and P. Jin, “A 3D reconstruction method for pipeline inspection based on multi-vision,” Measurement 98, 35–48 (2017).
[Crossref]

Opt. Express (2)

Other (13)

A. S. Metronor, Homepage, “Metronor One,” (Metronor, 2011–2018), http://www.metronor.com .

Gesellschaft für optische Messtechnik mbH Homepage, “ATOS Core – Optical 3D Scanner,” (GOM, 2011–2018), https:// www.gom.com/metrology-systems/atos/atos-core.html .

W. Bösemann, “Industrial photogrammetry-accepted METROLOGY tool or exotic niche,” presented at the International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, Prague, Czech Republic,12–19 July. (2016).

AICON 3D Systems GmbH Homepage, “Aicon-scanner,” (AICON, 2011–2018), https://www.aicon3d.com/de-DE/products/aicon-scanner .

AICON 3D Systems GmbH Homepage, “Tubeinspect,”(AICON, 2011–2018), https://www.aicon3d.com/de-DE/products/tubeinspect .

T. Zhang, J. Liu, C. Tang, and S. Liu, “3D reconstruction method of bent tube with NURBS curve,” in 2nd International Conference on Mechatronics and Applied Mechanics (ICMAM2012), C.K. Wang and J.Guo, ed. (Applied Mechanics and Materials, 2013), pp. 112–118.
[Crossref]

Y. Wei and A. Thornton, “Tube production and assembly systems: the impact of compliance and variability on yield,” presented at Design Engineering Technical Conferences and Computer and Information in Engineering Conference, Baltimore, Maryland, 10–13 Sept. (2000).

Extreme Networks white paper, “Virtual metropolitan area networks,” (Extreme Networks, 2001), http://www.extremenetworks.com/technology/whitepapers/vMAN.asp .

C. Doignon and M. de Mathelin, “A degenerate conic-based method for a direct fitting and 3-d pose of cylinders with a single perspective view,” in Proceedings of IEEE International Conference on Robotics and Automation, (IEEE, 2007), pp. 4220–4225.
[Crossref]

C. Liu and W. Hu, “Relative pose estimation for cylinder-shaped spacecrafts using single image,” in IEEE Transactions on Aerospace and Electronic Systems, (IEEE, 2014), pp. 3036–3056.

W. Bösemann, “The optical tube measurement system OLM photogrammetric methods used for industrial automation and process control,” presented at International Archives of Photogrammetry and Remote Sensing, Part B5, Vienna (1996).

I.-K. Lee and K.-J. Kim, “Shrinking: Another method for surface reconstruction,” in Geometric Modeling and Processing, 2004. Proceedings, (IEEE, 2004), pp. 259–266.

Caglioti and A. Giusti, “Reconstruction of canal surfaces from single images under exact perspective,” in European Conference on Computer Vision, A. Prinz, ed. (Springer, 2006), pp. 289–300.

Cited By

OSA participates in Crossref's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (9)

Fig. 1
Fig. 1 Projection error of bent tube axis.
Fig. 2
Fig. 2 Perspective projection model of arbitrary cross sectionn.
Fig. 3
Fig. 3 Projected process of coupled contour points.
Fig. 4
Fig. 4 Procedure of bent tube axis reconstruction.
Fig. 5
Fig. 5 Binocular vision measurement system.
Fig. 6
Fig. 6 Result for tube with diameter about 6 mm. (a) Tube to be measured; (b) Reconstruction result.
Fig. 7
Fig. 7 Result for tube with diameter about 15 mm. (a) Tube to be measured; (b) Reconstruction result.
Fig. 8
Fig. 8 Result for tube with diameter about 24 mm. (a) Tube to be measured; (b) Reconstruction result.
Fig. 9
Fig. 9 Measurement results of bent tube images with noise.

Tables (10)

Tables Icon

Table 1 Calibration results of binocular stereo visual sensors

Tables Icon

Table 2 Results of the tube with about 6 mm diameter

Tables Icon

Table 3 Results of the tube with about 15 mm diameter

Tables Icon

Table 4 Results of the tube with about 24 mm diameter

Tables Icon

Table 5 Results of the tube with about 6 mm diameter by traditional method

Tables Icon

Table 6 Comparison results of two methods

Tables Icon

Table 7 Results of the tube with about 15mm diameter by traditional method

Tables Icon

Table 8 Comparison results of two methods

Tables Icon

Table 9 Results of the tube with about 24 mm diameter by traditional method

Tables Icon

Table 10 Comparison results of two methods

Equations (11)

Equations on this page are rendered with MathJax. Learn more.

P ˜ 1 = k 1 [ A 1 0 ] T P ˜ 1 ' + [ 0 0 0 1 ] T
B= A 1 =[ b 11 b 12 b 13 b 21 b 22 b 23 b 31 b 32 b 33 ]
[ X 1 Y 1 Z 1 ]=[ k 1 ( b 11 x 1 + b 12 y 1 + b 13 ) k 1 ( b 21 x 1 + b 22 y 1 + b 23 ) k 1 ( b 31 x 1 + b 32 y 1 + b 33 ) ]=[ k 1 γ 11 k 1 γ 12 k 1 γ 13 ]
[ X 1 Y 1 Z 1 ]=[ γ 11 / ( n 1 γ 11 + n 2 γ 12 + n 3 γ 13 ) d γ 12 / ( n 1 γ 11 + n 2 γ 12 + n 3 γ 13 ) d γ 13 / ( n 1 γ 11 + n 2 γ 12 + n 3 γ 13 ) d ]=[ η 11 d η 12 d η 13 d ]
P ˜ c = k c [ B 0 ] T P ˜ c ' + [ 0 0 0 1 ] T
[ k c n 1 k c n 2 k c n 3 T 31 T 32 T 33 k c ( η 11 η 21 ) k c ( η 12 η 22 ) k c ( η 13 η 23 ) ][ θ 1 θ 2 θ 3 ]=d[ 1 0 Ω ]
{ B P ˜ c ' = [ θ 1 θ 2 θ 3 ] T 1/2 ( η 11 2 η 21 2 + η 12 2 η 22 2 + η 13 2 η 23 2 )=Ω
[ ψ 1 ψ 2 ψ 3 ] T =n 1 Ω [ η 11 η 21 η 12 η 22 η 13 η 23 ] T
( [ ψ 1 ψ 2 ψ 3 T 31 T 32 T 33 ]B ) P ˜ c ' =0
P ˜ 1 ' T ω V ˜ h P ˜ 1 ' T ω P ˜ 1 ' V ˜ h T ω V ˜ h = P ˜ 2 ' T ω V ˜ h P ˜ 2 ' T ω P ˜ 2 ' V ˜ h T ω V ˜ h
J c ( P 1 ' , P 2 ' )= [ arccos( P ˜ 1 ' T ω V ˜ h P ˜ 1 ' T ω P ˜ 1 ' V ˜ h T ω V ˜ h )arccos( P ˜ 2 ' T ω V ˜ h P ˜ 2 ' T ω P ˜ 2 ' V ˜ h T ω V ˜ h ) ] 2

Metrics