文章基本信息

标题：AUTOMATIC CLASSIFICATION OF POINT CLOUDS FOR HIGHWAY DOCUMENTATION
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作者：Martina Hůlková ; Karel Pavelka ; Eva Matoušková 等
期刊名称：Acta Polytechnica
印刷版ISSN：1210-2709
电子版ISSN：1805-2363
出版年度：2018
卷号：58
期号：3
DOI：10.14311/AP.2018.58.0165
语种：English
出版社：Czech Technical University in Prague
摘要：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.
关键词：mobile laser scanning;road inventory;classification;image processing