Abstract
An approach for building detection and feature lines extraction from airborne LiDAR data is proposed in this paper. The building detection is based on Wavelet Transform and geometric properties of buildings, and the extraction of feature lines is based on Hough Transform and image processing. Although LiDAR data contains rich surface information, the shortcoming is it cannot capture building features such as corners, edges, faces of roofs directly. For data-driven building reconstruction, the feature lines are essential to reconstruct the roof models. The basic idea of the proposed approach is to detect the location of each single building in the raw LiDAR data firstly. Then, the initial feature lines which are divided into external contour lines and internal structure lines are extracted respectively. The external contour lines are extracted using Hough Transform, and the internal structure lines are extracted using collinear analysis. Finally, the roof models are reconstructed by external contour lines as well as the internal structure lines of buildings. The experiment results showed that the regular and simple roofs such as rectangle roofs, gabled roofs and L-type roofs could be reconstructed successfully.
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