• DocumentCode
    147703
  • Title

    Automatic extraction method study of road marking lines based on projection of point clouds

  • Author

    Yuan Yao ; Qingwu Hu

  • Author_Institution
    Sch. of Remote Sensing & Inf. Eng., Wuhan Univ., Wuhan, China
  • fYear
    2014
  • fDate
    25-27 June 2014
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Quick access and updates of urban road network information is an important part of construction and management. With the rapid development of urban cities, traditional surveying and mapping with long operation cycle and slow data updating as its characteristics already cannot meet the requirements. To solve the problem, this paper puts forward an automatic extraction method of road lines based on Vehicle-borne laser scanning point data. First, transforms point clouds into image based on intensity projection; Second, uses some simple methods to process the image, which are erosion, dilation, sharpen edges and binarization; third, extracts road lines in image space by using Hough Transform; finally, searches the points around the road line from point clouds, and then extracts road lines through least squares fitting Method automatically. After a series of experiments, it turns out that road line extraction accuracy is up to 0.04m, which obviously shows that this method has broad application prospects in urban road network database building and updating.
  • Keywords
    edge detection; feature extraction; intelligent transportation systems; roads; Hough transform; automatic extraction method; binarization; dilation; erosion; least squares fitting method; point clouds projection; road lines automatic extraction method; road marking lines; sharpen edges; urban road network; vehicle-borne laser scanning point data; Image edge detection; Roads; Standards; Hough Transform; Least Squares; projection; vehicle-borne laser scanning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoinformatics (GeoInformatics), 2014 22nd International Conference on
  • Conference_Location
    Kaohsiung
  • ISSN
    2161-024X
  • Type

    conf

  • DOI
    10.1109/GEOINFORMATICS.2014.6950816
  • Filename
    6950816