Paper
19 May 2006 Segmentation and classification of airborne laser scanner data for ground and building detection
Gustav Tolt, Åsa Persson, Jonas Landgård, Ulf Söderman
Author Affiliations +
Abstract
In this paper, a number of techniques for segmentation and classification of airborne laser scanner data are presented. First, a method for ground estimation is described, that is based on region growing starting from a set of ground seed points. In order to prevent misclassification of buildings and vegetation as ground, a number of non-ground regions are first extracted, in which seed points should be discarded. Then, a decision-level fusion approach for building detection is proposed, in which the outputs of different classifiers are combined in order to improve the final classification results. Finally, a technique for building reconstruction is briefly outlined. In addition to being a tool for creating 3D building models, it also serves as a final step in the building classification process since it excludes regions not belonging to any roof segment in the final building model.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gustav Tolt, Åsa Persson, Jonas Landgård, and Ulf Söderman "Segmentation and classification of airborne laser scanner data for ground and building detection", Proc. SPIE 6214, Laser Radar Technology and Applications XI, 62140C (19 May 2006); https://doi.org/10.1117/12.665451
Lens.org Logo
CITATIONS
Cited by 16 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image segmentation

Vegetation

3D modeling

Laser scanners

Data modeling

Image fusion

Astatine

Back to Top