University of Wollongong
Browse

File(s) not publicly available

Rotation axis calibration of a 3D scanning system based on dual-turntable angle cancellation

journal contribution
posted on 2024-11-17, 13:24 authored by Limei Song, Zhenning Liu, Yunpeng Li, Qinghua Guo, Jinshen He, Jipeng Zhang
Rotation axis calibration is crucial for high-precision automatic point cloud stitching in turntable-based 3D scanning systems. To achieve a 360◦ sampling with a 2D calibrator in rotation axis calibration, this paper proposes a dual-turntable angle cancellation (DTAC) method. DTAC introduces an auxiliary turntable to keep a proper relative angle between the 3D sensor and the calibrator during the calibration process. The auxiliary turntable rotates at the same and opposite angle as the main turntable and cancels the increment of the relative angle. By projecting the feature points on the planar calibrator from real-world space to virtual calibration space, the projected points all share the same rotation axis of the main turntable. Further, a layered circle center extraction (LCCE) algorithm is applied to deal with outlier data points. The algorithm uses a two-step robust estimation strategy combining RANSAC circle fitting with a median noise filter for circle center selection. The standard ball reconstruction experiment shows that the 3D system calibrated by the method achieves a mean absolute error of 0.022 mm and root mean square error of 0.025 mm within the measurement distance of 60–70 cm. Point cloud stitching experiments of different types of objects show that our method outperforms other state-of-the-art methods in stitching accuracy. The DTAC method and LCCE algorithm can improve turntable-based 3D scanning systems.

Funding

National Natural Science Foundation of China (TD13-5036)

History

Journal title

Applied Optics

Volume

62

Issue

4

Pagination

894-903

Language

English

Usage metrics

    Categories

    No categories selected

    Keywords

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC