Automated road marking detection system for autonomous car
In recent years, road markings detection has received great attention and has been widely explored due to the aim of producing a system that is able to detect various shape of road markings on the images that are captured under various imaging conditions. Generally, the road images are captured usin...
Saved in:
Main Authors: | , , |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
IEEE
2015
|
Online Access: | http://psasir.upm.edu.my/id/eprint/57677/1/Automated%20road%20marking%20detection%20system%20for%20autonomous%20car.pdf http://psasir.upm.edu.my/id/eprint/57677/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.upm.eprints.57677 |
---|---|
record_format |
eprints |
spelling |
my.upm.eprints.576772017-12-28T03:40:53Z http://psasir.upm.edu.my/id/eprint/57677/ Automated road marking detection system for autonomous car Khan, Bahadur Shah Hanafi, Marsyita Mashohor, Syamsiah In recent years, road markings detection has received great attention and has been widely explored due to the aim of producing a system that is able to detect various shape of road markings on the images that are captured under various imaging conditions. Generally, the road images are captured using a camera, which has been placed inside the vehicle at a fixed position. However, the quality of the resulting images decreases if the camera position has been changed accidentally, due to the movement of the car. Hence, in this paper, a road markings detection system that tackle the problems of detecting road markings on the images captured under various camera positions and illumination conditions is proposed. The system consists of a graph cut segmentation method, which is used to detect the road, an inverse perspective transform method, which is used to convert the image into a bird's-eye view image, an image normalization method, which is CLAHE and a connected component analysis that is used to remove the background. We demonstrate the usefulness of the constructed algorithm by performing experiments on a database that consists of 400 road images. IEEE 2015 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/57677/1/Automated%20road%20marking%20detection%20system%20for%20autonomous%20car.pdf Khan, Bahadur Shah and Hanafi, Marsyita and Mashohor, Syamsiah (2015) Automated road marking detection system for autonomous car. In: 2015 IEEE Student Conference on Research and Development (SCOReD), 13-14 Dec. 2015, Berjaya Times Square Hotel, Kuala Lumpur, Malaysia. (pp. 398-401). 10.1109/SCORED.2015.7449364 |
institution |
Universiti Putra Malaysia |
building |
UPM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Putra Malaysia |
content_source |
UPM Institutional Repository |
url_provider |
http://psasir.upm.edu.my/ |
language |
English |
description |
In recent years, road markings detection has received great attention and has been widely explored due to the aim of producing a system that is able to detect various shape of road markings on the images that are captured under various imaging conditions. Generally, the road images are captured using a camera, which has been placed inside the vehicle at a fixed position. However, the quality of the resulting images decreases if the camera position has been changed accidentally, due to the movement of the car. Hence, in this paper, a road markings detection system that tackle the problems of detecting road markings on the images captured under various camera positions and illumination conditions is proposed. The system consists of a graph cut segmentation method, which is used to detect the road, an inverse perspective transform method, which is used to convert the image into a bird's-eye view image, an image normalization method, which is CLAHE and a connected component analysis that is used to remove the background. We demonstrate the usefulness of the constructed algorithm by performing experiments on a database that consists of 400 road images. |
format |
Conference or Workshop Item |
author |
Khan, Bahadur Shah Hanafi, Marsyita Mashohor, Syamsiah |
spellingShingle |
Khan, Bahadur Shah Hanafi, Marsyita Mashohor, Syamsiah Automated road marking detection system for autonomous car |
author_facet |
Khan, Bahadur Shah Hanafi, Marsyita Mashohor, Syamsiah |
author_sort |
Khan, Bahadur Shah |
title |
Automated road marking detection system for autonomous car |
title_short |
Automated road marking detection system for autonomous car |
title_full |
Automated road marking detection system for autonomous car |
title_fullStr |
Automated road marking detection system for autonomous car |
title_full_unstemmed |
Automated road marking detection system for autonomous car |
title_sort |
automated road marking detection system for autonomous car |
publisher |
IEEE |
publishDate |
2015 |
url |
http://psasir.upm.edu.my/id/eprint/57677/1/Automated%20road%20marking%20detection%20system%20for%20autonomous%20car.pdf http://psasir.upm.edu.my/id/eprint/57677/ |
_version_ |
1643836558958133248 |
score |
13.211869 |