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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...

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Bibliographic Details
Main Author: Ahmad, Amirul
Format: Thesis
Language:English
Published: 2021
Subjects:
Aerial geography
Road and highway design
Online Access:http://ir.uitm.edu.my/id/eprint/43728/1/43728.pdf
http://ir.uitm.edu.my/id/eprint/43728/
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spelling my.uitm.ir.437282021-03-19T03:18:32Z http://ir.uitm.edu.my/id/eprint/43728/ Assessment of automated road features xtraction algorithm from UAV images / Amirul Ahmad 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. 2021-03-18 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/43728/1/43728.pdf Ahmad, Amirul (2021) Assessment of automated road features xtraction algorithm from UAV images / Amirul Ahmad. Degree thesis, Universiti Teknologi Mara Perlis.
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
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
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
publishDate 2021
url http://ir.uitm.edu.my/id/eprint/43728/1/43728.pdf
http://ir.uitm.edu.my/id/eprint/43728/
_version_ 1695534703364276224
score 13.211869

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