关键词: 张量投票, 机载LiDAR点云, 道路骨架线, 最小尺度因子, 多层特征显著性

Abstract:

Aiming at the noise interference in detecting road centerlines from airborne LiDAR data, with multi-feature road saliency, a road centerline extraction method based on the minimum scale factor determined by the maximum road width to cast tensor voting algorithm is proposed. The pre-processed three-dimensional road point clouds are transformed into a two-dimensional intensity image. Ball voting is executed with the minimum scale factor to eliminate the road edge parts with polarity. To enhance the salient linear features, ball and stick tensor votings are carried out on the road image to fill the gaps and smooth the boundary with the recalculated minimum scale factor. The accurate road centerlines are obtained by thinning algorithm. Compared with the mathematical morphology method, tensor voting algorithm can extract road centerlines with higher accuracy from the noisy image.

Key words: tensor voting, airborne LiDAR data, road centerlines, the minimum scale factor, multi-feature saliency