Road extraction from 3D point clouds based on the difference of normal vector

Siwen Quan; Yue Xin; Yuxin Cheng; Meng Hui

doi:10.1117/12.2623170

16 February 2022 Road extraction from 3D point clouds based on the difference of normal vector

Siwen Quan, Yue Xin, Yuxin Cheng, Meng Hui

Proceedings Volume 12083, Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021); 120831E (2022) https://doi.org/10.1117/12.2623170
Event: Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021), 2021, Kunming, China

Abstract

Mobile Laser System and Airborne Laser System can quickly collect a large quantity of urban scene point cloud data in real time, the collected point cloud data is the main source of road area extraction. However, the obtained point cloud data are redundant and unordered discrete, which are challenging for efficient classification and extraction. In order to solve these problems, we propose a road extraction method based on the difference of normal vector: 1) preprocess the data for simplifying the point cloud, making the subsequent operations more efficiently; 2) use the progressive morphological filter to obtain the ground point cloud data, and then calculate the difference of normal vector for the clusters of the point cloud to get the preliminary road area; 3) leverage the random sample consensus plane fitting method to optimize the road area. The experimental results show that the proposed method can extract the road area accurately and quickly from the urban 3D point cloud data.

Citation Download Citation

Siwen Quan, Yue Xin, Yuxin Cheng, and Meng Hui "Road extraction from 3D point clouds based on the difference of normal vector", Proc. SPIE 12083, Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021), 120831E (16 February 2022); https://doi.org/10.1117/12.2623170

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KEYWORDS

Clouds

Roads

Optical filters

Buildings

Feature extraction

Data modeling

Image filtering

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