Hybrid algorithms of laser scanning point cloud for topological analysis

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

Abstract

Laser scanning technologies are widely used to solve civil engineering problems and land use management in a GIS environment including digital terrain models (DTMs) creation. Some gaps in raw laser scanning data processing algorithms for DTM are analyzed. Algorithms for filtration, triangulation, and defragmentation are proposed. Advantages and disadvantages of the algorithms proposed are discussed. Triangulation algorithm can serve to defragment cloud of laser scanning points into semantic component parts. Defragmentation includes recognition of engineering objects and other objects of the terrain and their delineation. Results of applications to real problems show the robustness of algorithms proposed.

LanguageEnglish
Title of host publicationAdvances in Intelligent Systems and Computing
PublisherSpringer
Pages223-234
Number of pages12
DOIs
StatePublished - 1 Jan 2019

Publication series

NameAdvances in Intelligent Systems and Computing
Volume797
ISSN (Print)2194-5357

Keywords

  • Algorithm
  • Cloud of points
  • Digital terrain model
  • Laser scanning
  • Triangulation

Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Badenko, V., Fedotov, A., & Vinogradov, K. (2019). Hybrid algorithms of laser scanning point cloud for topological analysis. In Advances in Intelligent Systems and Computing (pp. 223-234). (Advances in Intelligent Systems and Computing; Vol. 797). Springer. https://doi.org/10.1007/978-981-13-1165-9_20
Badenko, Vladimir ; Fedotov, Alexander ; Vinogradov, Konstantin. / Hybrid algorithms of laser scanning point cloud for topological analysis. Advances in Intelligent Systems and Computing. Springer, 2019. pp. 223-234 (Advances in Intelligent Systems and Computing).
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Badenko, V, Fedotov, A & Vinogradov, K 2019, Hybrid algorithms of laser scanning point cloud for topological analysis. in Advances in Intelligent Systems and Computing. Advances in Intelligent Systems and Computing, vol. 797, Springer, pp. 223-234. https://doi.org/10.1007/978-981-13-1165-9_20

Hybrid algorithms of laser scanning point cloud for topological analysis. / Badenko, Vladimir; Fedotov, Alexander; Vinogradov, Konstantin.

Advances in Intelligent Systems and Computing. Springer, 2019. p. 223-234 (Advances in Intelligent Systems and Computing; Vol. 797).

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

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AB - Laser scanning technologies are widely used to solve civil engineering problems and land use management in a GIS environment including digital terrain models (DTMs) creation. Some gaps in raw laser scanning data processing algorithms for DTM are analyzed. Algorithms for filtration, triangulation, and defragmentation are proposed. Advantages and disadvantages of the algorithms proposed are discussed. Triangulation algorithm can serve to defragment cloud of laser scanning points into semantic component parts. Defragmentation includes recognition of engineering objects and other objects of the terrain and their delineation. Results of applications to real problems show the robustness of algorithms proposed.

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Badenko V, Fedotov A, Vinogradov K. Hybrid algorithms of laser scanning point cloud for topological analysis. In Advances in Intelligent Systems and Computing. Springer. 2019. p. 223-234. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-981-13-1165-9_20