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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...

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Main Authors: Bong, David B L, Lai, K.C., Joseph, A.
Format: E-Article
Language:English
Published: WASET 2009
Subjects:
TA Engineering (General). Civil engineering (General)
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
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spelling my.unimas.ir.177992017-09-27T03:14:53Z http://ir.unimas.my/id/eprint/17799/ Automatic Road Network Recognition and Extraction for Urban Planning Bong, David B L Lai, K.C. Joseph, A. TA Engineering (General). Civil engineering (General) 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. WASET 2009 E-Article PeerReviewed text en http://ir.unimas.my/id/eprint/17799/1/Automatic%20Road%20Network%20Recognition%20%28abstract%29.pdf Bong, David B L and Lai, K.C. and Joseph, A. (2009) Automatic Road Network Recognition and Extraction for Urban Planning. International Science Index, Civil and Environmental Engineering, 3 (5). ISSN 2409-0441 https://www.researchgate.net/publication/255574786
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Bong, David B L
Lai, K.C.
Joseph, A.
Automatic Road Network Recognition and Extraction for Urban Planning
description 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.
format E-Article
author Bong, David B L
Lai, K.C.
Joseph, A.
author_facet Bong, David B L
Lai, K.C.
Joseph, A.
author_sort Bong, David B L
title Automatic Road Network Recognition and Extraction for Urban Planning
title_short Automatic Road Network Recognition and Extraction for Urban Planning
title_full Automatic Road Network Recognition and Extraction for Urban Planning
title_fullStr Automatic Road Network Recognition and Extraction for Urban Planning
title_full_unstemmed Automatic Road Network Recognition and Extraction for Urban Planning
title_sort automatic road network recognition and extraction for urban planning
publisher WASET
publishDate 2009
url 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
_version_ 1644512711881523200
score 13.23648

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