A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Automatic Crack Detection on Pavement Images for Monitoring Road Surface Conditions—Some Results from the Collaborative FP7 TRIMM Project
Abstract This paper presents the two image processing techniques that have been developed within the scope of the TRIMM project to automatically detect pavement cracking from images. The first technique is a heuristic approach (HA) which was originally developed to process pavement images from the French imaging device. The Minimal Path Selection (MPS) method is a new technique which provides the accurate segmentation of the crack pattern along with the estimation of the crack width. HA has been assessed against the field data collection over UK roads provided by Yotta and TRL using the Tempest 2 device. MPS has been assessed against Aigle-RN pavement images over the French network. The benchmarking of five automatic segmentation techniques has been provided at both the pixel and the grid levels. Among others, MPS reached the best performance at the pixel level while it is matched to the FFA method at the grid level.
Automatic Crack Detection on Pavement Images for Monitoring Road Surface Conditions—Some Results from the Collaborative FP7 TRIMM Project
Abstract This paper presents the two image processing techniques that have been developed within the scope of the TRIMM project to automatically detect pavement cracking from images. The first technique is a heuristic approach (HA) which was originally developed to process pavement images from the French imaging device. The Minimal Path Selection (MPS) method is a new technique which provides the accurate segmentation of the crack pattern along with the estimation of the crack width. HA has been assessed against the field data collection over UK roads provided by Yotta and TRL using the Tempest 2 device. MPS has been assessed against Aigle-RN pavement images over the French network. The benchmarking of five automatic segmentation techniques has been provided at both the pixel and the grid levels. Among others, MPS reached the best performance at the pixel level while it is matched to the FFA method at the grid level.
Automatic Crack Detection on Pavement Images for Monitoring Road Surface Conditions—Some Results from the Collaborative FP7 TRIMM Project
Baltazart, V. (author) / Moliard, J.-M. (author) / Amhaz, R. (author) / Cottineau, L.-M. (author) / Wright, A. (author) / Wright, D. (author) / Jethwa, M. (author)
2016-01-01
6 pages
Article/Chapter (Book)
Electronic Resource
English
Automatic road crack detection from pavement images
| DataCite | 2024
Crack detection from pavement images
| DataCite | 2024
Automatic pavement crack filling device for road engineering
| European Patent Office | 2021