Techniques for fisheye lens calibration using a minimal number of measurements

Terrell Nathan Mundhenk; Michael J. Rivett; Xiaoqun Liao; Ernest L. Hall

doi:10.1117/12.403762

11 October 2000 Techniques for fisheye lens calibration using a minimal number of measurements

Terrell Nathan Mundhenk, Michael J. Rivett, Xiaoqun Liao, Ernest L. Hall

Proceedings Volume 4197, Intelligent Robots and Computer Vision XIX: Algorithms, Techniques, and Active Vision; (2000) https://doi.org/10.1117/12.403762
Event: Intelligent Systems and Smart Manufacturing, 2000, Boston, MA, United States

Abstract

A method is discussed describing how different types of Omni-Directional fisheye lenses can be calibrated for use in robotic vision. The technique discussed will allow for full calibration and correction of x,y pixel coordinates while only taking two uncalibrated and one calibrated measurement. These are done by finding the observed x,y coordinates of a calibration target. Any Fisheye lense that has a roughly spherical shape can have its distortion corrected with this technique. Two measurements are taken to discover the edges and centroid of the lens. These can be done automatically by the computer and does not require any knowledge about the lens or the location of the calibration target. A third measurement is then taken to discover the degree of spherical distortion. This is done by comparing the expected measurement to the measurement obtained and then plotting a curve that describes the degree of distortion. Once the degree of distortion is known and a simple curve has been fitted to the distortion shape, the equation of that distortion and the simple dimensions of the lens are plugged into an equation that remains the same for all types of lenses. The technique has the advantage of needing only one calibrated measurement to discover the type of lens being used.

Citation Download Citation

Terrell Nathan Mundhenk, Michael J. Rivett, Xiaoqun Liao, and Ernest L. Hall "Techniques for fisheye lens calibration using a minimal number of measurements", Proc. SPIE 4197, Intelligent Robots and Computer Vision XIX: Algorithms, Techniques, and Active Vision, (11 October 2000); https://doi.org/10.1117/12.403762

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