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Automated recognition of 3D pipelines from point clouds

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A Correction to this article was published on 01 July 2020

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Abstract

This study proposes a method for detecting and reconstructing pipelines from a 3D point cloud. First, the method extracts points on cylindrical objects using various properties computed with the principal curvatures. Next, the possible radii of the cylinders in the point cloud are estimated using a histogram constructed with the radii of the curvature at each point. Once the candidate radii are obtained, spheres are estimated using a RANdom SAmple Consensus-based algorithm, whose centroids are processed to find the orientation and centerline of each cylinder. The nearest cylindrical components which are detected are then analyzed to establish connectivity to determine how they are arranged in space. Depending on the type of connectivity, elbows and/or T-junctions are used to connect the cylindrical elements to form pipelines. The proposed method was tested with synthetic and scanned point clouds and demonstrated better performance than that of the existing methods.

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Availability of data and material (data transparency)

The data that support the findings of this study are available on request from the corresponding author, Kwanghee Ko. Part of the data are not publicly available due to a restriction, e.g., their containing information that could compromise the privacy of research participants.

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Funding

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (2017R1A2B4012124).

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Authors and Affiliations

  1. The School of Mechanical Engineering, Gwangju Institute of Science and Technology, 1 Oryeongdong, Bukgu, Gwangju, 500-712, Republic of Korea

    Inyoung Oh & Kwang Hee Ko

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  1. Inyoung Oh
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  2. Kwang Hee Ko
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by IO and KK. The first draft of the manuscript was written by IO and KK, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Kwang Hee Ko.

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The authors declare that they have no conflict of interest.

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The programs developed in the work are available upon request as long as they as a whole or part of them are not used for any commercial purposes.

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The original version of this article was revised: The spelling of the name of author Kwang Hee Ko was wrong.

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Oh, I., Ko, K.H. Automated recognition of 3D pipelines from point clouds. Vis Comput 37, 1385–1400 (2021). https://doi.org/10.1007/s00371-020-01872-y

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