Camera calibration with a near-parallel imaging system based on geometric moments

JunLan Li; DaWei Zhang

doi:10.1117/1.3533032

1 February 2011 Camera calibration with a near-parallel imaging system based on geometric moments

JunLan Li, DaWei Zhang

Author Affiliations +

Funded by: National Science Foundation of China, Tianjin Science and Technology Commission Projects

Optical Engineering, Vol. 50, Issue 2, 023601 (February 2011). https://doi.org/10.1117/1.3533032

Abstract

This paper presents a novel approach of camera calibration under the near-parallel condition based on geometric moments. The near-parallel condition means that the calibration board is near parallel (or parallel) to the imaging plane. A camera calibration model for the near-parallel condition and a calibration board with arranged rectangular features are suggested. Before calibration, feature regions on the image of calibration board are extracted, and centroid and rotation of each feature are detected using geometric moments. These centroids are used for feature points, and meanwhile mean value of rotations is used for the rotation around axis Z. Then, the closed-form solutions to the translations, other two angles and effective focal length are provided by combining Gauss lens model with camera model. Subsequently, principal point is received by radial alignment constraint (RAC), and distortion coefficients are calculated. Finally, all camera parameters are refined by a nonlinear minimization procedure according to the distortion coefficients. Simulations and experiments are performed to verify the proposed camera calibration algorithm. The precision of detecting feature points and calibrating camera parameters are analyzed. The precision of camera calibration results is also evaluated.

©(2011) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

JunLan Li and DaWei Zhang "Camera calibration with a near-parallel imaging system based on geometric moments," Optical Engineering 50(2), 023601 (1 February 2011). https://doi.org/10.1117/1.3533032

Published: 1 February 2011

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