Camera calibration and orientation for PCB jet printing inspection

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Abstract

To assess the quality of printed solder joints in the jet printing of printed circuit boards, a calibrated camera is used to reconstruct the solder volume via photogrammetry as a specific task of computer vision. This requires a procedure for calibration and orientation determination due to restrictions within the image acquisition process. We herein consider a novel application area called an ultra-close range normal case photogrammetry, where a camera acquires small objects at small operating distances and fields of depth. Because the camera cannot rotate or translate in the z-direction, we propose and evaluate four calibration procedures in terms of their capability in a normal case calibration within the ultra-close range. To set up an optimal calibration pipeline, a three-dimensional (3D) calibration field is used for single and multi-image calibrations. To enhance the accuracy and to simplify the assignment of 3D coordinates to the detected markers, we propose a geometry-based estimation of the lens model to undistort the image points. Close-range applications utilize spacer rings and extension tubes to enlarge the magnification and reduce the operating distance. We also examine the influence of these extensions on the intrinsics of the camera and the reconstruction result. Additionally, we demonstrate the dependence of the accuracy on the lens model in terms of radial and tangential distortions and the number of distortion coefficients regarding the reprojection error ϵrepro. Finally, we provide recommendations for a lens configuration for ultra-close range normal case calibrations and measurements, based on the calibration and reconstruction results, which are evaluated by the 2D reprojection error ϵrepro and the 3D reconstruction error ϵrecon obtained from a second independent calibration field.

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Heinemann, D., Dutz, S., Knabner, S., Haueisen, J., & Baumgarten, D. (2020). Camera calibration and orientation for PCB jet printing inspection. SN Applied Sciences, 2(3). https://doi.org/10.1007/s42452-020-2087-7

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