Openly accessible

Vision-based pavement marking detection and condition assessment-a case study

Xu, S, Wang, Jun, Wu, P, Shou, W, Wang, X and Chen, M 2021, Vision-based pavement marking detection and condition assessment-a case study, Applied Sciences (Switzerland), vol. 11, no. 7, pp. 1-16, doi: 10.3390/app11073152.

Attached Files
Name Description MIMEType Size Downloads

Title Vision-based pavement marking detection and condition assessment-a case study
Author(s) Xu, S
Wang, Jun
Wu, P
Shou, W
Wang, X
Chen, M
Journal name Applied Sciences (Switzerland)
Volume number 11
Issue number 7
Article ID 3152
Start page 1
End page 16
Total pages 16
Publisher MDPI
Place of publication Basel, Switzerland
Publication date 2021
ISSN 2076-3417
Keyword(s) pavement management
line marking detection
audible marking
condition assessment
computer vision
Summary Pavement markings constitute an effective way of conveying regulations and guidance to drivers. They constitute the most fundamental way to communicate with road users, thus, greatly contributing to ensuring safety and order on roads. However, due to the increasingly extensive traffic demand, pavement markings are subject to a series of deterioration issues (e.g., wear and tear). Markings in poor condition typically manifest as being blurred or even missing in certain places. The need for proper maintenance strategies on roadway markings, such as repainting, can only be determined based on a comprehensive understanding of their as-is worn condition. Given the fact that an efficient, automated and accurate approach to collect such condition information is lacking in practice, this study proposes a vision-based framework for pavement marking detection and condition assessment. A hybrid feature detector and a threshold-based method were used for line marking identification and classification. For each identified line marking, its worn/blurred severity level was then quantified in terms of worn percentage at a pixel level. The damage estimation results were compared to manual measurements for evaluation, indicating that the proposed method is capable of providing indicative knowledge about the as-is condition of pavement markings. This paper demonstrates the promising potential of computer vision in the infrastructure sector, in terms of implementing a wider range of managerial operations for roadway management.
Language eng
DOI 10.3390/app11073152
Indigenous content off
HERDC Research category C1 Refereed article in a scholarly journal
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30150285

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 14 Abstract Views, 1 File Downloads  -  Detailed Statistics
Created: Thu, 22 Apr 2021, 09:29:50 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.