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
Link To Document