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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: Joseph N. Mait
  • Vol. 51, Iss. 5 — Feb. 10, 2012
  • pp: 588–593

Self-consistent way to determine relative distortion of axial symmetric lens systems

Sukmock Lee, Robert Parks, and James H. Burge  »View Author Affiliations


Applied Optics, Vol. 51, Issue 5, pp. 588-593 (2012)
http://dx.doi.org/10.1364/AO.51.000588


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Abstract

We present a simple method to determine the relative distortion of axially symmetric lens systems. This method uses graphs to determine every parametric value instead of nonlinear minimization computation and is composed of an LCD screen to display a square grid pattern of pixel-wide spots and a set of analyzing processes for the spots in the image. The two Cartesian components of the spot locations are processed by a two-step linear least-square fitting to third-order polynomials. The graphs for the coefficients enable us to determine the amount of decentering of the camera lens axis with respect to the center of the image array and the tip/tilt of the screen, which in turn gives the relative distortion coefficient. We present experimental results to demonstrate the utility of the method by comparing our results with the corresponding values determined by open source software available online.

© 2012 Optical Society of America

OCIS Codes
(120.4800) Instrumentation, measurement, and metrology : Optical standards and testing
(150.1488) Machine vision : Calibration

ToC Category:
Instrumentation, Measurement, and Metrology

History
Original Manuscript: August 17, 2011
Revised Manuscript: October 21, 2011
Manuscript Accepted: October 21, 2011
Published: February 7, 2012

Citation
Sukmock Lee, Robert Parks, and James H. Burge, "Self-consistent way to determine relative distortion of axial symmetric lens systems," Appl. Opt. 51, 588-593 (2012)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-51-5-588


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References

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  8. W. T. Wellford, Aberrations of Optical Systems (Adam Hilger, 1986), p. 126.
  9. O. Faugeras, Three-Dimensional Computer Vision: A Geometric Viewpoint (MIT, 1993).
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