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High-Precision Lens Distortion Correction Using Smoothed Thin Plate Splines

  • Sönke Schmid
  • Xiaoyi Jiang
  • Klaus Schäfers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8048)

Abstract

Lens distortion and its modelling is an important factor for the calibration of optical cameras. Most calibration algorithms include a distortion model to cope with the discrepancy to a pinhole camera model induced by the camera lenses. However, for high-precision calibration sophisticated distortion models have to be used and their often numerous parameters have to be determined during calibration. In this work we present a simple, nonparametric method based on smoothed thin plate splines for correcting the lens distortion with a very high precision.

Keywords

optical camera calibration lens distortion 

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References

  1. 1.
    Devernay, F.: A Non-Maxima Suppression Method for Edge Detection with Sub-Pixel Accuracy. INRIA Research Rep. 2724 (1995)Google Scholar
  2. 2.
    Devernay, F., Faugeras, O.: Straight lines have to be straight: automatic calibration and removal of distortion from scenes of structured enviroments. Mach. Vision Appl., 14–24 (2001)Google Scholar
  3. 3.
    Duchon, J.: Splines minimizing rotation-invariant semi-norms in Sobolev spaces. Lecture Notes in Mathematics, vol. 571, pp. 85–100 (1977)Google Scholar
  4. 4.
    Claus, D., Fitzgibbon, A.-W.: A Rational Function Lens Distortion Model for General Cameras. In: Proc. IEEE Conf. on Comp. Vis. and Pattern Rec., pp. 213–219 (2005)Google Scholar
  5. 5.
    Grompone von Gioi, R., Monasse, P., Morel, J.-M., Tang, Z.: Towards high-precision lens distortion correction. In: 17th IEEE Int. Conf. on Im. Proc., pp. 4237–4240 (2010)Google Scholar
  6. 6.
    Grompone von Gioi, R., Monasse, P., Morel, J.-M., Tang, Z.: Lens distortion correction with a calibration harp. In: Proc. 18th Int. Conf. on Im. Proc., pp. 617–620 (2011)Google Scholar
  7. 7.
    Goshtasby, A.: Correction of image deformation from lens distortion using bezier patches. Comput. Vision Graph. Image Process. 47, 385–399 (1989)CrossRefGoogle Scholar
  8. 8.
    Ma, L., Chen, Y.Q., Moore, K.L.: Analytical piecewise radial distortion model for precision camera calibration. Proc. on Vis., Im. and Sign. 153, 468–474 (2006)CrossRefGoogle Scholar
  9. 9.
    Mallon, J., Whelan, P.F.: Which pattern? Biasing aspects of planar calibration patterns and detection methods. Pattern Recognition Letters 28, 921–930 (2007)CrossRefGoogle Scholar
  10. 10.
    Mühlich, M., Aach, T.: High accuracy feature detection for camera calibration: a multi-steerable approach. In: Proc. of 29th DAGM conf. on Pattern rec., pp. 284–293 (2007)Google Scholar
  11. 11.
    Schaefer, S., McPhail, T., Warren, J.: Image deformation using moving least squares. ACM Trans. Graph. 25, 533–540 (2006)CrossRefGoogle Scholar
  12. 12.
    Sun, W., Zhou, W., Yang, M.: Non-rigid registration of medical images with scale-space corner detection and thin-plate spline. Biomed. Sign. Proc. 7, 599–605 (2012)CrossRefGoogle Scholar
  13. 13.
    Wahba, G.: Spline models for observational data. In: Soc. for Ind. and App. Math. CBMS-NSF Reg. Conf. Series in App. Math (SIAM), vol. 59 (1990)Google Scholar
  14. 14.
    Zhang, Z.: A Flexible New Technique for Camera Calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22, 1330–1334 (2000)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Sönke Schmid
    • 1
    • 2
    • 3
  • Xiaoyi Jiang
    • 1
    • 2
    • 3
  • Klaus Schäfers
    • 2
    • 3
  1. 1.Dept. of Mathematics and Computer ScienceUniversity of MünsterGermany
  2. 2.European Institute for Molecular ImagingUniversity of MünsterGermany
  3. 3.Cluster of Excellence EXC 1003Cells in Motion, CiMMünsterGermany

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