ORIGINAL RESEARCH article
Adv. Opt. Technol.
Sec. Optical Imaging
Volume 14 - 2025 | doi: 10.3389/aot.2025.1670919
The implementation of point cloud registration based on rotating landmark platform
Provisionally accepted
- 1Wuyi University, Jiangmen, China
- 2Jiangmen Polytechnic, Jiangmen, China
- 3University of Wollongong, Wollongong, Australia
- 4Macau University of Science and Technology, Taipa, Macao, SAR China
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ABSTRACT Point cloud registration is the key step to obtain the final cloud data in the 3D shape measurement based on the structured light projection. The existing point cloud registration method based on landmark points will bring inconvenience to operation, while the point cloud registration method without landmark points is high computation cost. In order to achieve fast and accurate point cloud matching, a point cloud registration method based on a rotating landmark point platform is proposed in this paper. First of all, the image features of white landmark points which are randomly pasted on the rotating platform in two-dimensional images are analyzed, enabling the effective removal of image noises and allowing for the accurate synthesis of the center of landmark points. Then, the geometric features of the angle of the rotating marker platform are analyzed, a new method is proposed to find the matching markers quickly and accurately. The proposed method efficiently locates the position of the landmark points on the rotating platform and achieves precise point cloud registration when combined with the ICP algorithm. To sum up, the registration scheme of multiple point clouds is improved, the fast and accurate registration is realized and the final overall 3D data of the object is obtained. This paper verified the feasibility of this method by automatic registration of two groups of point clouds with different angles.
Keywords: Rotating landmark platform, point cloud registration, 3D measurement, ICP algorithm, Singular Value Decomposition Algorithm
Received: 22 Jul 2025; Accepted: 09 Oct 2025.
Copyright: © 2025 Zhang, Long, Fu, Du, Weng, Xi, Deng and Peng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jiale Long, longjiale_528@126.com
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