Assessment of automated road features xtraction algorithm from UAV images / Amirul Ahmad

In these days, thorough documentation of the road network is vital. It is especially true for many applications such as managing transportation and automation of navigation. Therefore, the extraction of road network such as from Unmanned Aerial Vehicle (UAV) imagery is needed so that it can be made...

Full description

Saved in:

Bibliographic Details
Main Author:	Ahmad, Amirul
Format:	Thesis
Language:	English
Published:	2021
Subjects:	Aerial geography Road and highway design
Online Access:	https://ir.uitm.edu.my/id/eprint/43728/1/43728.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-uitm-ir.43728
record_format	uketd_dc
spelling	my-uitm-ir.437282021-03-19T03:18:32Z Assessment of automated road features xtraction algorithm from UAV images / Amirul Ahmad 2021-03-18 Ahmad, Amirul Aerial geography Road and highway design In these days, thorough documentation of the road network is vital. It is especially true for many applications such as managing transportation and automation of navigation. Therefore, the extraction of road network such as from Unmanned Aerial Vehicle (UAV) imagery is needed so that it can be made use for these applications. The road network extraction can be done manually, however, it is costly and time consuming to update and utilize the spatial information compared to automatic extraction. The aim of this study is to analyze the capabilities of automatic road extraction from UAV images using Trainable Weka Segmentation (TWS), Level Set (LS) and Seeded Region Growing (SRG) method. To achieve this, the objectives of this study are to: 1) extract road automatically using TWS, LS and SRG method and 2) examine the capabilities of automatic road extraction from UAV images. The study area was carried out at UiTM Arau, Perlis, Malaysia. To ensure the completion of all objectives, several Ground Control Points (GCPs) had been established at UiTM Arau. Lastly, Agisoft PhotoScan had been used to build the orthophoto which then the road network in the orthophoto had been segmented and extracted using these ImageJ Fiji. The automatic extracted road network had then been compared to manually extracted road network. It was found that SRG method is slightly better in extracting road features compared to LS method. This study can help reducing the cost and time consumed in extracting features, especially road network, by using automatic extraction instead of manual extraction. 2021-03 Thesis https://ir.uitm.edu.my/id/eprint/43728/ https://ir.uitm.edu.my/id/eprint/43728/1/43728.pdf text en public degree Universiti Teknologi Mara Perlis Faculty of Architecture, Planning and Surveying
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Aerial geography Road and highway design
spellingShingle	Aerial geography Road and highway design Ahmad, Amirul Assessment of automated road features xtraction algorithm from UAV images / Amirul Ahmad
description	In these days, thorough documentation of the road network is vital. It is especially true for many applications such as managing transportation and automation of navigation. Therefore, the extraction of road network such as from Unmanned Aerial Vehicle (UAV) imagery is needed so that it can be made use for these applications. The road network extraction can be done manually, however, it is costly and time consuming to update and utilize the spatial information compared to automatic extraction. The aim of this study is to analyze the capabilities of automatic road extraction from UAV images using Trainable Weka Segmentation (TWS), Level Set (LS) and Seeded Region Growing (SRG) method. To achieve this, the objectives of this study are to: 1) extract road automatically using TWS, LS and SRG method and 2) examine the capabilities of automatic road extraction from UAV images. The study area was carried out at UiTM Arau, Perlis, Malaysia. To ensure the completion of all objectives, several Ground Control Points (GCPs) had been established at UiTM Arau. Lastly, Agisoft PhotoScan had been used to build the orthophoto which then the road network in the orthophoto had been segmented and extracted using these ImageJ Fiji. The automatic extracted road network had then been compared to manually extracted road network. It was found that SRG method is slightly better in extracting road features compared to LS method. This study can help reducing the cost and time consumed in extracting features, especially road network, by using automatic extraction instead of manual extraction.
format	Thesis
qualification_level	Bachelor degree
author	Ahmad, Amirul
author_facet	Ahmad, Amirul
author_sort	Ahmad, Amirul
title	Assessment of automated road features xtraction algorithm from UAV images / Amirul Ahmad
title_short	Assessment of automated road features xtraction algorithm from UAV images / Amirul Ahmad
title_full	Assessment of automated road features xtraction algorithm from UAV images / Amirul Ahmad
title_fullStr	Assessment of automated road features xtraction algorithm from UAV images / Amirul Ahmad
title_full_unstemmed	Assessment of automated road features xtraction algorithm from UAV images / Amirul Ahmad
title_sort	assessment of automated road features xtraction algorithm from uav images / amirul ahmad
granting_institution	Universiti Teknologi Mara Perlis
granting_department	Faculty of Architecture, Planning and Surveying
publishDate	2021
url	https://ir.uitm.edu.my/id/eprint/43728/1/43728.pdf
_version_	1783734700631654400

Assessment of automated road features xtraction algorithm from UAV images / Amirul Ahmad

Similar Items