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Title: DEVELOPMENT OF ALGORITHMS FOR POINT CLOUD FILTRATION
DEVELOPMENT OF ALGORITHMS FOR POINT CLOUD FILTRATION

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Richard Honti; Jan Erdelyi; Alojz Kopacik
10.5593/sgem2022/2.1/s10.37
10.5593/sgem2022/2.1
1314-2704
978-619-7603-40-8
English
22
2.1
•    Prof. DSc. Oleksandr Trofymchuk, UKRAINE 
•    Prof. Dr. hab. oec. Baiba Rivza, LATVIA
Photogrammetry and Remote Sensing
Today, point clouds are becoming an increasingly common digital representation of realworld objects. However, the raw point clouds obtained by terrestrial laser scanning (or other methods, e. g., photogrammetry or low-cost sensors) are often noisy with many outliers. Thus, it is necessary to remove the noise and outliers from the point clouds before further processing while preserving the elements of the measured objects in high detail. Moreover, in the case of model creation from point clouds using basic geometric shapes (e.g., planes, spheres, cylinders, etc.), one of the most important processing steps is the segmentation of these shapes. Therefore, filtration of unrelated parts of the point cloud can increase the efficiency of processing. In this paper, two algorithms for point cloud filtration are developed, which can be performed based on the local point density and the local normal variation in the surrounding of the selected point. The algorithms were implemented as a standalone application in MATLAB software. The paper's final part describes the experimental testing of the proposed algorithms on several point clouds with various densities, complexity, and different levels of noise and outliers.
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This work was supported by the Slovak Research and Development Agency under the Contract no. APVV-18-0247.
conference
https://doi.org/10.5593/sgem2022/2.1/s10.37
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Proceedings of 22nd International Multidisciplinary Scientific GeoConference SGEM 2022
22nd International Multidisciplinary Scientific GeoConference SGEM 2022, 04 - 10 July, 2022
Proceedings Paper
STEF92 Technology
International Multidisciplinary Scientific GeoConference SGEM
SWS Scholarly Society; Acad Sci Czech Republ; Latvian Acad Sci; Polish Acad Sci; Serbian Acad Sci and Arts; Natl Acad Sci Ukraine; Natl Acad Sci Armenia; Sci Council Japan; European Acad Sci, Arts and Letters; Acad Fine Arts Zagreb Croatia; Croatian Acad Sci and Arts; Acad Sci Moldova; Montenegrin Acad Sci and Arts; Georgian Acad Sci; Acad Fine Arts and Design Bratislava; Turkish Acad Sci.
323-330
04 - 10 July, 2022
website
8505
terrestrial laser scanning, point cloud, point cloud processing, noise filtration, outlier removal