测绘通报 ›› 2018, Vol. 0 ›› Issue (8): 97-101.doi: 10.13474/j.cnki.11-2246.2018.0253

• 技术交流 • 上一篇    下一篇

融合空谱特征的车载LiDAR点云道路标识线提取

范雯, 何鄂龙, 李天琪, 孙杰   

  1. 中国地质大学(武汉)信息工程学院, 湖北 武汉 430074
  • 收稿日期:2018-04-26 修回日期:2018-06-11 出版日期:2018-08-25 发布日期:2018-08-30
  • 通讯作者: 孙杰。E-mail:sunjie_cug@163.com E-mail:sunjie_cug@163.com
  • 作者简介:范雯(1997-),女,主要研究方向为点云分割。E-mail:wfan@cug.edu.cn
  • 基金资助:
    秦岭及天山等重点成矿区带航空物探调查(121201203000160006)

Lane Marking Extraction for MLS Data Based on Space-spectral Feature

FAN Wen, HE Elong, LI Tianqi, SUN Jie   

  1. School of Information Engineering, China University of Geoscience, Wuhan 430074, China
  • Received:2018-04-26 Revised:2018-06-11 Online:2018-08-25 Published:2018-08-30

摘要: 道路标识线是三维道路场景中重要的交通标识之一。自动提取点云场景中的标识线信息对于道路路宽测量、自动驾驶等任务具有十分重要的意义。本文提出了一种基于空谱特征的车载LiDAR点云道路标识线提取方法。该方法充分考虑车载激光点云中道路标识线的颜色、空间邻域和高程等位置关系,直接对点云数据进行自动分类,提取道路标识线。为了验证本文方法的有效性,采用高速公路路段场景的车载激光点云数据进行试验,从中选取训练数据及测试区域进行道路标识线提取试验。最后,本文基于手动标记数据验证本文方法的效果,道路标识线提取总体精度为99.64%。

关键词: 车载激光扫描, 点云, 空谱, 高差, 空间分布

Abstract: The lane marking is very important for the 3D road scene.Automatic extraction of lane marking in the point cloud scene is of great significance for tasks like the measurement of road width and automatic driving.This paper proposed a space-spactral feature for the extraction of lane marking from mobile LiDAR point cloud.This method fully considers the relationship between color,spatial neighborhood and elevation within lane marking point cloud,which aims to classify the point cloud data and extract lane marking.In order to confirm the effectiveness of this method,a highway scene mobile laser point cloud data with manual labeling is used for the experiments,the training data sets and test data sets are selected for the lane marking extraction experiments.The overall accuracy of road markings extraction is 99.64%,which proves the effectiveness of proposed method.

Key words: mobile laser scanning, point cloud, space-spectral feature, height difference, spatial distribution

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