Image-Based Automated Width Measurement of Surface Cracking

The detection of cracks is an important monitoring task in civil engineering infrastructure devoted to ensuring durability, structural safety, and integrity. It has been traditionally performed by visual inspection, and the measurement of crack width has been manually obtained with a crack-width com...

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Autores principales:	Miguel Carrasco, Gerardo Araya-Letelier, Ramiro Velázquez, Paolo Visconti
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	surface cracks crack characterization infrastructure durability assessment Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/c4f7180798b54ced85d0be150a8dad3e
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id	oai:doaj.org-article:c4f7180798b54ced85d0be150a8dad3e
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spelling	oai:doaj.org-article:c4f7180798b54ced85d0be150a8dad3e2021-11-25T18:57:13ZImage-Based Automated Width Measurement of Surface Cracking10.3390/s212275341424-8220https://doaj.org/article/c4f7180798b54ced85d0be150a8dad3e2021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/22/7534https://doaj.org/toc/1424-8220The detection of cracks is an important monitoring task in civil engineering infrastructure devoted to ensuring durability, structural safety, and integrity. It has been traditionally performed by visual inspection, and the measurement of crack width has been manually obtained with a crack-width comparator gauge (CWCG). Unfortunately, this technique is time-consuming, suffers from subjective judgement, and is error-prone due to the difficulty of ensuring a correct spatial measurement as the CWCG may not be correctly positioned in accordance with the crack orientation. Although algorithms for automatic crack detection have been developed, most of them have specifically focused on solving the segmentation problem through Deep Learning techniques failing to address the underlying problem: crack width evaluation, which is critical for the assessment of civil structures. This paper proposes a novel automated method for surface cracking width measurement based on digital image processing techniques. Our proposal consists of three stages: anisotropic smoothing, segmentation, and stabilized central points by k-means adjustment and allows the characterization of both crack width and curvature-related orientation. The method is validated by assessing the surface cracking of fiber-reinforced earthen construction materials. The preliminary results show that the proposal is robust, efficient, and highly accurate at estimating crack width in digital images. The method effectively discards false cracks and detects real ones as small as 0.15 mm width regardless of the lighting conditions.Miguel CarrascoGerardo Araya-LetelierRamiro VelázquezPaolo ViscontiMDPI AGarticlesurface crackscrack characterizationinfrastructure durability assessmentChemical technologyTP1-1185ENSensors, Vol 21, Iss 7534, p 7534 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	surface cracks crack characterization infrastructure durability assessment Chemical technology TP1-1185
spellingShingle	surface cracks crack characterization infrastructure durability assessment Chemical technology TP1-1185 Miguel Carrasco Gerardo Araya-Letelier Ramiro Velázquez Paolo Visconti Image-Based Automated Width Measurement of Surface Cracking
description	The detection of cracks is an important monitoring task in civil engineering infrastructure devoted to ensuring durability, structural safety, and integrity. It has been traditionally performed by visual inspection, and the measurement of crack width has been manually obtained with a crack-width comparator gauge (CWCG). Unfortunately, this technique is time-consuming, suffers from subjective judgement, and is error-prone due to the difficulty of ensuring a correct spatial measurement as the CWCG may not be correctly positioned in accordance with the crack orientation. Although algorithms for automatic crack detection have been developed, most of them have specifically focused on solving the segmentation problem through Deep Learning techniques failing to address the underlying problem: crack width evaluation, which is critical for the assessment of civil structures. This paper proposes a novel automated method for surface cracking width measurement based on digital image processing techniques. Our proposal consists of three stages: anisotropic smoothing, segmentation, and stabilized central points by k-means adjustment and allows the characterization of both crack width and curvature-related orientation. The method is validated by assessing the surface cracking of fiber-reinforced earthen construction materials. The preliminary results show that the proposal is robust, efficient, and highly accurate at estimating crack width in digital images. The method effectively discards false cracks and detects real ones as small as 0.15 mm width regardless of the lighting conditions.
format	article
author	Miguel Carrasco Gerardo Araya-Letelier Ramiro Velázquez Paolo Visconti
author_facet	Miguel Carrasco Gerardo Araya-Letelier Ramiro Velázquez Paolo Visconti
author_sort	Miguel Carrasco
title	Image-Based Automated Width Measurement of Surface Cracking
title_short	Image-Based Automated Width Measurement of Surface Cracking
title_full	Image-Based Automated Width Measurement of Surface Cracking
title_fullStr	Image-Based Automated Width Measurement of Surface Cracking
title_full_unstemmed	Image-Based Automated Width Measurement of Surface Cracking
title_sort	image-based automated width measurement of surface cracking
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/c4f7180798b54ced85d0be150a8dad3e
work_keys_str_mv	AT miguelcarrasco imagebasedautomatedwidthmeasurementofsurfacecracking AT gerardoarayaletelier imagebasedautomatedwidthmeasurementofsurfacecracking AT ramirovelazquez imagebasedautomatedwidthmeasurementofsurfacecracking AT paolovisconti imagebasedautomatedwidthmeasurementofsurfacecracking
_version_	1718410551529308160

Image-Based Automated Width Measurement of Surface Cracking

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