Skip to main content
SpringerLink
Log in

A sub-pixel stereo matching algorithm and its applications in fabric imaging

  • Original Paper
  • Published:
Machine Vision and Applications Aims and scope Submit manuscript

Abstract

In this paper, we describe a sub-pixel stereo matching algorithm where disparities are iteratively refined within a regularization framework. We choose normalized cross-correlation as the matching metric, and perform disparity refinement based on correlation gradients, which is distinguished from intensity gradient-based methods. We propose a discontinuity-preserving regularization technique which utilizes local coherence in the disparity space image, instead of estimating discontinuities in the intensity images. A concise numerical solution is derived by parameterizing the disparity space with dense bicubic B-splines. Experimental results show that the proposed algorithm performs better than correlation fitting methods without regularization. The algorithm has been implemented for applications in fabric imaging. We have shown its potentials in wrinkle evaluation, drape measurement, and pilling assessment.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Abidi, N., Hequet, E., Turner, C., Sari-Sarraf, H.: Objective evaluation of durable press treatment and fabric smoothness ratings. Text. Res. J. 75(1), 19–29 (2005)

    Article  Google Scholar 

  2. Anandan, P.: A computational framework and an algorithm for the measurement of visual motion. Int. J. Comput. Vis. 2, 283–310 (1989)

    Article  Google Scholar 

  3. Aschwanden, P., Guggenbuhl, W.: Experimental results from a comparative study on correlation-type registration algorithms. In: Forstner, W., Ruwiedel, S. (eds) Robust Computer Vision, pp. 268–289. Wickmann, Karlsruhe (1993)

    Google Scholar 

  4. Boykov, Y., Veksler, O., Zabih, R.: Fast approximation energy minimization via graph cuts. IEEE Trans. Pattern Anal. Mach. Intell. 23(11), 1222–1239 (2001)

    Article  Google Scholar 

  5. Brown, M.Z., Burschka, D., Hager, G.D.: Advances in computational stereo. IEEE Trans. Pattern Anal. Mach. Intell. 25(8), 993–1008 (2003)

    Article  Google Scholar 

  6. Dhond, U., Aggarwal, J.K.: Structure from stereo—a review. IEEE Trans. Syst. Man Cyber. 19(6), 1489–1510 (1989)

    Article  MathSciNet  Google Scholar 

  7. Faugeras, O., Keriven, R.: Variational principles, surface evolution, PDE’s, level set methods, and the stereo problem. IEEE Trans. Image Process. 7(3), 336–344 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  8. Geiger, D., Ladendorf, B., Yuille, A.: Occlusions and binocular stereo. Int. J. Comput. Vis. 14, 211–226 (1996)

    Article  Google Scholar 

  9. Gong, M., Yang, Y.-H.: Genetic-based stereo algorithm and disparity map evaluation. Int. J. Comput. Vision 47(1/2/3), 63–77 (2002)

    Article  MATH  Google Scholar 

  10. Hu, J., Xin, B., Yan, H.: Measuring and modeling 3D wrinkles in fabrics. Text. Res. J. 72(10), 863–869 (2002)

    Article  Google Scholar 

  11. Kang, T.J., Cho, D.H., Kim, S.M.: Objective evaluation of fabric pilling using stereovision. Text. Res. J. 74(11), 1013–1017 (2004)

    Article  Google Scholar 

  12. Kang, T.J., Cho, D.H., Whang, H.S.: A new objective method of measuring fabric wrinkles using a 3D projecting grid technique. Text. Res. J. 69(4), 261–268 (1999)

    Article  Google Scholar 

  13. Kolmogorov, V., Zabih, R.: Computing visual correspondence with occlusions using graph cuts. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 508–515, July (2001)

  14. Lucas, B.D., Kanade, T.: An iterative image registration technique with an application to stereo vision. In: Processings of the 7th International Joint Conference on Artificial Intelligence, Vancouver, pp. 674–679 (1981)

  15. Nehab, D., Rusinkiewicz, S. Davis, J.: Improved sub-pixel stereo correspondences through symmetric refinement. International Conference on Computer Vision (ICCV), 1, 557–563, October 2005

  16. Piegl, L.: On NURBS: A survey. IEEE Comput. Graph. Appl. 11(1), 55–71 (1991)

    Article  Google Scholar 

  17. Piegl, L., Tiller, W.: The NURBS Book, Monographs in Visual Communications, 2nd edn. Springer, Berlin (1997)

    Google Scholar 

  18. Poggio, T., Torre, V., Koch, C.: Computational vision and regularization theory. Nature 317(26), 314–319 (1985)

    Article  Google Scholar 

  19. Roy, S.: Stereo without epipolar lines: A maximum-flow formulation. Int. J. Comput. Vis. 34(2/3), 147–161 (1999)

    Article  Google Scholar 

  20. Scharstein, D., Szeliski, R.: A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. Int. J. Comput. Vis. 47(1/2/3), 7–42 (2002)

    Article  MATH  Google Scholar 

  21. Shimizu, M., Okutomi, M.: Sub-pixel estimation error cancellation on area-based matching. Int. J. Comput. Vis. 63(3), 207–224 (2005)

    Article  Google Scholar 

  22. Su, J., Xu, B.: Fabric winkle evaluation using laser triangulation and neural network classifier. Opt. Eng. 38(10), 1688–1693 (1999)

    Article  Google Scholar 

  23. Sun, C.: Fast stereo matching using rectangular subregioning and 3D maximum-surface techniques. Int. J. Comput. Vis. 47(1/2/3), 99–117 (2002)

    Article  MATH  Google Scholar 

  24. Sun, J., Li, Y., Kang, S.B., Shum, H.-Y.: Symmetric stereo matching for occlusion handling. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 399–406, June (2005)

  25. Sun, J., Zheng, N.-N., Shum, H.-Y.: Stereo matching using belief propagation. IEEE Trans. Pattern Anal. Mach. Intell. 25(7), 787–800 (2003)

    Article  Google Scholar 

  26. Szeliski, R., Coughlan, J.: Spline-based image registration. Int. J. Comp. Vis. 22(3), 199–218 (1997)

    Article  Google Scholar 

  27. Szeliski, R., Scharstein, D.: Symmetric sub-pixel stereo matching. In: Proceedings of the 7th European Conference on Computer Vision, pp. 525–540, Copenhagen (2002)

  28. Tardon-Garcia, L.-J., Portillo-Garcia, J., Alberola-Lopez, C.: Markov random field and the disparity gradient constraint applied to stereo correspondence. In: Proceedings of 1999 International Conference on Image Processing, vol. 3, 901–905 (1999)

  29. Terzopoulos, D.: Regularization of inverse visual problems involving discontinuities. IEEE Trans. Pattern Anal. Mach. Intell. 8(4), 413–424 (1986)

    Article  Google Scholar 

  30. Unser, M., Aldroubi, A., Eden, M.: Fast B-spline transforms for continuous image representation and interpolation. IEEE Trans. Pattern Anal. Mach. Intell. 13, 277–285 (1991)

    Article  Google Scholar 

  31. Wei, G.-Q., Brauer, W., Hirzinger, G.: Intensity- and gradient-based stereo matching using hierarchical Gaussian basis functions. IEEE Trans. Pattern Anal. Mach. Intell. 20(11), 1143–1160 (1998)

    Article  Google Scholar 

  32. Westerweel, J.: Digital Particle Image Velocimetry: Theory and Application. Delft University Press, Delft (1993)

    Google Scholar 

  33. Xin, B., Hu, J., Yan, H.: Objective evaluation of fabric pilling using image analysis techniques. Text. Res. J. 72(12), 1057–1064 (2002)

    Article  Google Scholar 

  34. Xu, B.: Instrumental evaluation of fabric pilling. J. Text. Inst. 88, 488–500 (1997)

    Google Scholar 

  35. Xu, B., Cuminato, D.F.: Evaluation of fabric smoothness appearance using a laser profilometer. Text. Res. J. 68(12), 900–906 (1998)

    Article  Google Scholar 

  36. Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, 78712, USA

    Wurong Yu & Bugao Xu

Authors
  1. Wurong Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bugao Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bugao Xu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Yu, W., Xu, B. A sub-pixel stereo matching algorithm and its applications in fabric imaging. Machine Vision and Applications 20, 261–270 (2009). https://doi.org/10.1007/s00138-007-0121-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00138-007-0121-z

Keywords

Search

Navigation