Automatic Crack Detection on Pavement Images for Monitoring Road Surface Conditions—Some Results from the Collaborative FP7 TRIMM Project

Baltazart, Vincent; Moliard, J.-M.; Amhaz, Rabih; Cottineau, L-M; Wright, Ann E.; Wright, D.; Jethwa, Manish

doi:10.1007/978-94-024-0867-6_100

Cited by 4 publications

(3 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Evaluation of road structures is of major importance to maintain their durability and extend their lifetime [1]. Damages due to heavy traffic may result from a weak or defective bonding between asphalt layers [2,3].…”

Section: Introductionmentioning

confidence: 99%

GPR Monitoring of Artificial Debonded Pavement Structures throughout Its Life Cycle during Accelerated Pavement Testing

et al. 2021

View full text Add to dashboard Cite

The paper gives an overview of a ground penetrating radar (GPR) experiment to survey debonding areas within pavement structure during accelerated pavement tests (APT) conducted on the university Gustave Eiffel’s fatigue carrousel. Thirteen artificial defect sections composed of three types of defects (Tack-free, Geotextile, and Sand-based) were embedded during the construction phase between the top and the base layers. The data were collected in two stages covering the entire life cycle of the pavement structure using four GPR systems: An air-coupled ultra-wideband GPR (SF-GPR), two wideband 2D ground coupled GPRs (a SIR-4000 with a 1.5 GHz antenna and a 2.6 GHz-StructureScan from GSSI manufacturer), and a wideband 3D GPR (from 3D-radar manufacturer). The first stage of the experiments took place in 2012–2013 and lasted up to 300 K loadings. During this stage, the pavement structure presented no clear degradation. The second stage of experiments was conducted in 2019 and continued until the pavement surface demonstrated a strong degradation, which was observed at 800 K loadings. At the end of the GPR experiments, several trenches were cut at various sections to get the ground truth of the pavement structure. Finally, the GPR data are processed using the conventional amplitude ratio test to study the evolution of the echoes coming from the debonded areas.

show abstract

Section: Introductionmentioning

confidence: 99%

GPR Monitoring of Artificial Debonded Pavement Structures throughout Its Life Cycle during Accelerated Pavement Testing

et al. 2021

View full text Add to dashboard Cite

show abstract

“…The pavement images can provide information on the presence of cracks through the pixel intensities and the shape of the darker image features. Many image processing techniques exist for the detection of cracking on grey level images, e.g., [4][5][6][7][8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

“…The benchmarking of some existing techniques is provided in [1,[4][5][6][7]. One of the latest technique, namely the Minimal Path Selection (MPS) technique has shown to outperform the other methods at the pixel scale on simulated and field pavement images.…”

Section: Introductionmentioning

confidence: 99%

Ongoing tests and improvements of the MPS algorithm for the automatic crack detection within grey level pavement images

Baltazart¹,

Nicolle²,

Yang

2017

2017 25th European Signal Processing Conference (EUSIPCO)

Self Cite

View full text Add to dashboard Cite

Abstract-The MPS approach (Minimal Path Selection) has shown in [1] to provide robust and accurate segmentation of cracks within pavement images compared to other algorithms. As a counterpart, MPS suffers from a large computing time. In this paper, we present three different ongoing improvements to reduce the computing time and to improve the overall segmentation performance. Most of the work focuses on the first three steps of the algorithm which achieve the segmentation of the crack skeleton. This is at first the improvement of the MPS methodology under Matlab coding, then, the C language MPS version and finally, the first attempt to parallelize MPS under the GPU platform. The results on pavement images illustrate the achieved improvements in terms of better segmentation and faster computational time.

show abstract

Digitized Measurement of the Cracking Index on the Facings of Concrete Structures

Moliard¹,

Baltazart²,

Berenger

et al. 2016

RILEM Bookseries

View full text Add to dashboard Cite

Automatic Crack Detection on Pavement Images for Monitoring Road Surface Conditions—Some Results from the Collaborative FP7 TRIMM Project

Cited by 4 publications

References 3 publications

GPR Monitoring of Artificial Debonded Pavement Structures throughout Its Life Cycle during Accelerated Pavement Testing

GPR Monitoring of Artificial Debonded Pavement Structures throughout Its Life Cycle during Accelerated Pavement Testing

Ongoing tests and improvements of the MPS algorithm for the automatic crack detection within grey level pavement images

Digitized Measurement of the Cracking Index on the Facings of Concrete Structures

Contact Info

Product

Resources

About