AUTOMATIC CLASSIFICATION OF POINT CLOUDS FOR HIGHWAY DOCUMENTATION

Authors

  • Martina Hůlková Department of Geomatics, Faculty of Civil Engineering, Czech Technical University in Prague
  • Karel Pavelka Department of Geomatics, Faculty of Civil Engineering, Czech Technical University in Prague
  • Eva Matoušková Department of Geomatics, Faculty of Civil Engineering, Czech Technical University in Prague

DOI:

https://doi.org/10.14311/AP.2018.58.0165

Keywords:

mobile laser scanning, road inventory, classification, image processing

Abstract

Mobile laser scanning systems confirmed the capability for detailed roadway documentation. Hand in hand with enormous datasets acquired by these systems is the increase in the demands on the fast and effective processing of these datasets. The crucial part of the roadway datasets processing, as well as in many other applications, is the extraction of objects of interest from point clouds. In this work, an approach to the rough classification of mobile laser scanning data based on raster image processing techniques is presented. The developed method offers a solution for a computationally low demanding classification of the highway environment. The aim of this method is to provide a background for the easier use of more sophisticated algorithms and a specific analysis. The method is evaluated using different metrics on a 1.8km long dataset obtained by LYNX Mobile Mapper over a highway.

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Published

2018-07-02

Issue

Vol. 58 No. 3 (2018)

Section

Articles

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How to Cite

Hůlková, M., Pavelka, K., & Matoušková, E. (2018). AUTOMATIC CLASSIFICATION OF POINT CLOUDS FOR HIGHWAY DOCUMENTATION. Acta Polytechnica, 58(3), 165-170. https://doi.org/10.14311/AP.2018.58.0165