Hybrid Procedure for Automated Detection of Cracking with 3D Pavement Data

Giuseppe Sollazzo, Sollazzo, Li, Wang, Bosurgi

Risultato della ricerca: Article

20 Citazioni (Scopus)

Abstract

Pavement cracks are considered a major indicator of pavement performance. Because traditional manual crack surveys are dangerous, time consuming, and expensive, technologies have been developed to collect high-speed pavement images, and numerous algorithms have been proposed to detect cracks on pavement surface. The latest PaveVision3D Ultra system (3D Ultra) has been implemented to achieve 30-kHz three-dimensional (3D) scanning rate for 1-mm resolution pavement surface data at highway speed up to 100 km/h (60  mi/h). This paper presents the application of a hybrid procedure for automated crack detection on 3D pavement data collected using 3D Ultra. The procedure combines three different methods, namely, the matched filtering (MF) to highlight the cracks, the tensor voting to determine the main directions of the cracks, and the minimum spanning tree to identify the crack paths. The authors provide comparisons with cracking-detection results from traditional edge detectors and reference crack maps produced by a semiautomated software. The experimental results, through performance measurements and a statistical point of view, show that the proposed algorithm is able to detect pavement cracks with high precision. Finally, this paper also discusses preliminary considerations for exploiting the MF features to evaluate the orientation of the various crack segments.
Lingua originaleEnglish
pagine (da-a)1-12
Numero di pagine12
RivistaJournal of Computing in Civil Engineering
Volume30
Stato di pubblicazionePublished - 2016

Fingerprint

Pavements
Cracks
Crack detection
Tensors
Detectors
Scanning

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Computer Science Applications

Cita questo

Hybrid Procedure for Automated Detection of Cracking with 3D Pavement Data. / Sollazzo, Giuseppe; Sollazzo; Li; Wang; Bosurgi.

In: Journal of Computing in Civil Engineering, Vol. 30, 2016, pag. 1-12.

Risultato della ricerca: Article

@article{7787531f162a4d5faf705c60e8dd224e,
title = "Hybrid Procedure for Automated Detection of Cracking with 3D Pavement Data",
abstract = "Pavement cracks are considered a major indicator of pavement performance. Because traditional manual crack surveys are dangerous, time consuming, and expensive, technologies have been developed to collect high-speed pavement images, and numerous algorithms have been proposed to detect cracks on pavement surface. The latest PaveVision3D Ultra system (3D Ultra) has been implemented to achieve 30-kHz three-dimensional (3D) scanning rate for 1-mm resolution pavement surface data at highway speed up to 100 km/h (60  mi/h). This paper presents the application of a hybrid procedure for automated crack detection on 3D pavement data collected using 3D Ultra. The procedure combines three different methods, namely, the matched filtering (MF) to highlight the cracks, the tensor voting to determine the main directions of the cracks, and the minimum spanning tree to identify the crack paths. The authors provide comparisons with cracking-detection results from traditional edge detectors and reference crack maps produced by a semiautomated software. The experimental results, through performance measurements and a statistical point of view, show that the proposed algorithm is able to detect pavement cracks with high precision. Finally, this paper also discusses preliminary considerations for exploiting the MF features to evaluate the orientation of the various crack segments.",
keywords = "Civil and Structural Engineering, Computer Science Applications1707 Computer Vision and Pattern Recognition, Crack detection, Matched filtering, Minimum spanning tree, Tensor voting, Three-dimensional (3D) pavement data",
author = "Giuseppe Sollazzo and Sollazzo and Li and Wang and Bosurgi",
year = "2016",
language = "English",
volume = "30",
pages = "1--12",
journal = "Journal of Computing in Civil Engineering",
issn = "0887-3801",
publisher = "American Society of Civil Engineers (ASCE)",

}

TY - JOUR

T1 - Hybrid Procedure for Automated Detection of Cracking with 3D Pavement Data

AU - Sollazzo, Giuseppe

AU - Sollazzo, null

AU - Li, null

AU - Wang, null

AU - Bosurgi, null

PY - 2016

Y1 - 2016

N2 - Pavement cracks are considered a major indicator of pavement performance. Because traditional manual crack surveys are dangerous, time consuming, and expensive, technologies have been developed to collect high-speed pavement images, and numerous algorithms have been proposed to detect cracks on pavement surface. The latest PaveVision3D Ultra system (3D Ultra) has been implemented to achieve 30-kHz three-dimensional (3D) scanning rate for 1-mm resolution pavement surface data at highway speed up to 100 km/h (60  mi/h). This paper presents the application of a hybrid procedure for automated crack detection on 3D pavement data collected using 3D Ultra. The procedure combines three different methods, namely, the matched filtering (MF) to highlight the cracks, the tensor voting to determine the main directions of the cracks, and the minimum spanning tree to identify the crack paths. The authors provide comparisons with cracking-detection results from traditional edge detectors and reference crack maps produced by a semiautomated software. The experimental results, through performance measurements and a statistical point of view, show that the proposed algorithm is able to detect pavement cracks with high precision. Finally, this paper also discusses preliminary considerations for exploiting the MF features to evaluate the orientation of the various crack segments.

AB - Pavement cracks are considered a major indicator of pavement performance. Because traditional manual crack surveys are dangerous, time consuming, and expensive, technologies have been developed to collect high-speed pavement images, and numerous algorithms have been proposed to detect cracks on pavement surface. The latest PaveVision3D Ultra system (3D Ultra) has been implemented to achieve 30-kHz three-dimensional (3D) scanning rate for 1-mm resolution pavement surface data at highway speed up to 100 km/h (60  mi/h). This paper presents the application of a hybrid procedure for automated crack detection on 3D pavement data collected using 3D Ultra. The procedure combines three different methods, namely, the matched filtering (MF) to highlight the cracks, the tensor voting to determine the main directions of the cracks, and the minimum spanning tree to identify the crack paths. The authors provide comparisons with cracking-detection results from traditional edge detectors and reference crack maps produced by a semiautomated software. The experimental results, through performance measurements and a statistical point of view, show that the proposed algorithm is able to detect pavement cracks with high precision. Finally, this paper also discusses preliminary considerations for exploiting the MF features to evaluate the orientation of the various crack segments.

KW - Civil and Structural Engineering

KW - Computer Science Applications1707 Computer Vision and Pattern Recognition

KW - Crack detection

KW - Matched filtering

KW - Minimum spanning tree

KW - Tensor voting

KW - Three-dimensional (3D) pavement data

UR - http://hdl.handle.net/10447/355687

UR - http://ascelibrary.org/cpo/resource/1/jccee5

M3 - Article

VL - 30

SP - 1

EP - 12

JO - Journal of Computing in Civil Engineering

JF - Journal of Computing in Civil Engineering

SN - 0887-3801

ER -