Abdellatif, M orcid.org/0000-0002-7641-4723, Peel, H orcid.org/0000-0002-9432-3438, Cohn, AG orcid.org/0000-0002-7652-8907 et al. (1 more author) (2020) Pavement Crack Detection from Hyperspectral Images Using a Novel Asphalt Crack Index. Remote Sensing, 12 (18). 3084. ISSN 2072-4292
Abstract
Detection of road pavement cracks is important and needed at an early stage to repair the road and extend its lifetime for maintaining city roads. Cracks are hard to detect from images taken with visible spectrum cameras due to noise and ambiguity with background textures besides the lack of distinct features in cracks. Hyperspectral images are sensitive to surface material changes and their potential for road crack detection is explored here. The key observation is that road cracks reveal the interior material that is different from the worn surface material. A novel asphalt crack index is introduced here as an additional clue that is sensitive to the spectra in the range 450–550 nm. The crack index is computed and found to be strongly correlated with the appearance of fresh asphalt cracks. The new index is then used to differentiate cracks from road surfaces. Several experiments have been made, which confirmed that the proposed index is effective for crack detection. The recall-precision analysis showed an increase in the associated F1-score by an average of 21.37% compared to the VIS2 metric in the literature (a metric used to classify pavement condition from hyperspectral data).
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/) |
Keywords: | pavement crack detection; pavement defect inspection; asphalt crack index; hyper-spectral imaging; autonomous road inspection |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Civil Engineering (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/N010523/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 25 Nov 2020 15:49 |
Last Modified: | 06 Jan 2025 12:32 |
Status: | Published |
Publisher: | MDPI |
Identification Number: | 10.3390/rs12183084 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:168356 |