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

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journal contribution
posted on 2021-01-01, 00:00 authored by S Xu, Jun Wang, P Wu, W Shou, X Wang, M Chen
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.

History

Journal

Applied Sciences (Switzerland)

Volume

11

Article number

3152

Pagination

1-16

Location

Basel, Switzerland

Open access

  • Yes

eISSN

2076-3417

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Issue

7

Publisher

MDPI

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