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Article

A New Adaptive Method for the Extraction of Steel Design Structures from an Integrated Point Cloud

1
Department of Geodesy, Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Narutowicza 11-12, 80-233 Gdansk, Poland
2
Geopartner Spolka Z Ograniczoną Odpowiedzialnością Spolka Komandytowa, ul. Rakoczego 31, 80-171 Gdańsk, Poland
*
Author to whom correspondence should be addressed.
Academic Editors: Alessandro Sabato, Adam Martowicz, Piotr Kohut and Krzysztof Holak
Sensors 2021, 21(10), 3416; https://doi.org/10.3390/s21103416
Received: 19 April 2021 / Revised: 5 May 2021 / Accepted: 10 May 2021 / Published: 14 May 2021
(This article belongs to the Collection Vision Sensors and Systems in Structural Health Monitoring)
The continuous and intensive development of measurement technologies for reality modelling with appropriate data processing algorithms is currently being observed. The most popular methods include remote sensing techniques based on reflected-light digital cameras, and on active methods in which the device emits a beam. This research paper presents the process of data integration from terrestrial laser scanning (TLS) and image data from an unmanned aerial vehicle (UAV) that was aimed at the spatial mapping of a complicated steel structure, and a new automatic structure extraction method. We proposed an innovative method to minimize the data size and automatically extract a set of points (in the form of structural elements) that is vital from the perspective of engineering and comparative analyses. The outcome of the research was a complete technology for the acquisition of precise information with regard to complex and high steel structures. The developed technology includes such elements as a data integration method, a redundant data elimination method, integrated photogrammetric data filtration and a new adaptive method of structure edge extraction. In order to extract significant geometric structures, a new automatic and adaptive algorithm for edge extraction from a random point cloud was developed and presented herein. The proposed algorithm was tested using real measurement data. The developed algorithm is able to realistically reduce the amount of redundant data and correctly extract stable edges representing the geometric structures of a studied object without losing important data and information. The new algorithm automatically self-adapts to the received data. It does not require any pre-setting or initial parameters. The detection threshold is also adaptively selected based on the acquired data. View Full-Text
Keywords: photogrammetry; TLS; UAV; steel structure; monitoring; integration; fusion photogrammetry; TLS; UAV; steel structure; monitoring; integration; fusion
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Figure 1

  • Externally hosted supplementary file 1
    Doi: 10.34808/szar-a523
    Description: Matlab code for method presented in the paper.
MDPI and ACS Style

Burdziakowski, P.; Zakrzewska, A. A New Adaptive Method for the Extraction of Steel Design Structures from an Integrated Point Cloud. Sensors 2021, 21, 3416. https://doi.org/10.3390/s21103416

AMA Style

Burdziakowski P, Zakrzewska A. A New Adaptive Method for the Extraction of Steel Design Structures from an Integrated Point Cloud. Sensors. 2021; 21(10):3416. https://doi.org/10.3390/s21103416

Chicago/Turabian Style

Burdziakowski, Pawel, and Angelika Zakrzewska. 2021. "A New Adaptive Method for the Extraction of Steel Design Structures from an Integrated Point Cloud" Sensors 21, no. 10: 3416. https://doi.org/10.3390/s21103416

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