Automatic Road Network Recognition and Extraction for Urban Planning
The uses of road map in daily activities are numerous but it is a hassle to construct and update a road map whenever there are changes. In Universiti Malaysia Sarawak, research on Automatic Road Extraction (ARE) was explored to solve the difficulties in updating road map. The research started wi...
Saved in:
Main Authors: | , , |
---|---|
Format: | E-Article |
Language: | English |
Published: |
WASET
2009
|
Subjects: | |
Online Access: | http://ir.unimas.my/id/eprint/17799/1/Automatic%20Road%20Network%20Recognition%20%28abstract%29.pdf http://ir.unimas.my/id/eprint/17799/ https://www.researchgate.net/publication/255574786 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | The uses of road map in daily activities are numerous
but it is a hassle to construct and update a road map whenever there
are changes. In Universiti Malaysia Sarawak, research on Automatic
Road Extraction (ARE) was explored to solve the difficulties in
updating road map. The research started with using Satellite Image
(SI), or in short, the ARE-SI project. A Hybrid Simple Colour Space
Segmentation & Edge Detection (Hybrid SCSS-EDGE) algorithm
was developed to extract roads automatically from satellite-taken
images. In order to extract the road network accurately, the satellite
image must be analyzed prior to the extraction process. The
characteristics of these elements are analyzed and consequently the
relationships among them are determined. In this study, the road
regions are extracted based on colour space elements and edge details
of roads. Besides, edge detection method is applied to further filter
out the non-road regions. The extracted road regions are validated by
using a segmentation method. These results are valuable for building
road map and detecting the changes of the existing road database.
The proposed Hybrid Simple Colour Space Segmentation and Edge
Detection (Hybrid SCSS-EDGE) algorithm can perform the tasks
fully automatic, where the user only needs to input a high-resolution
satellite image and wait for the result. Moreover, this system can
work on complex road network and generate the extraction result in
seconds. |
---|