Digital image processing as a tool for pavement distress evaluation

Georgopoulos, A.; Loizos, Andreas; Flouda, A.

doi:10.1016/0924-2716(95)91844-a

Cited by 42 publications

(24 citation statements)

References 2 publications

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“…The former evaluates individual pixels sequentially to determine the crack widths and positions (see e.g. [12]), while Digital Image Correlation entails the calculation of displacement vectors of uniformly spaced coordinates on the surface of a specimen [10]. Both methods however have the drawback that it only measures the cracks on the surface, and not the internal cracking structure.…”

Section: Crack Measuring Systemmentioning

confidence: 99%

A new approach for modelling the ingress of deleterious materials in cracked strain hardening cement-based composites

et al. 2015

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Strain-hardening cement-based composites (SHCC) are characterised by their tensile ductility and high strain capacity. Due to their intrinsically small crack widths, SHCC exhibit favourable transport conditions in the cracked state compared to conventional concrete for certain transport mechanisms, e.g. diffusion and permeation and thus a good durability potential In this paper the Ingress Potential Index model is proposed which is a novel way of expressing the potential ingress of deleterious materials into cracked SHCC with a single value taking into account the strain level, crack pattern and a chosen ingress process. For the demonstration of the model, experimental data of water transport and chloride penetration into cracked concrete was used in combination with observed SHCC crack patterns. The purpose of this paper is to present an approach which can be used for any crack-linked ingress process and different distributions of crack widths. Future work is required to verify this novel approach experimentally.

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Section: Crack Measuring Systemmentioning

confidence: 99%

A new approach for modelling the ingress of deleterious materials in cracked strain hardening cement-based composites

et al. 2015

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“…These studies often focus on methods that allow classification of crack types (Georgopoulos et al, 1995;Lee and Lee, 2004). However, in most digital image-processing algorithms for cracks, there has been a lack of approaches to the change detection of cracks (crack growth).…”

Section: Introductionmentioning

confidence: 99%

Monitoring Crack Changes in Concrete Structures

Sohn

Lim

Yun

et al. 2005

Comp-aided Civil Eng

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This study proposes a crack-monitoring system to quantify the change of cracks from multitemporal images during the monitoring period. A series of images were taken from an off-the-shelf digital camera. Concrete cracks were extracted from the digital images by employing a series of image-processing techniques. The image coordinates and orientation of same cracks can be changed since the position and direction of the portable camera vary at every exposure time. To monitor the crack changes (width and length), it is critical to transform the image coordinates of cracks extracted from each image into the same object coordinates of the concrete surface. In this study, such a geometric relationship was automatically recovered using the two-dimensional (2D) projective transformation based on the modified iterated Hough transform (MIHT) algorithm, the result of which solved the transformation parameters. To improve the computational operation of MIHT, regions of parameter estimation were also investigated. The developed algorithms were applied to monitor the crack of the concrete specimen. As a result, the change of cracks on the concrete specimen was successfully detected and accurately quantified.

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“…Chou et al [5] used moment invariants from different types of distress to obtain the features, and then used a back propagation neural network to classify the features. A. Georgopoulos, et al [6] proposed a method in which the distress can be represented by a set of vectors, approximating the cracks composing the distress. Then the direction vectors are grouped into two categories, horizontal and vertical, and the cracks are classified based on their presence.…”

Section: Introductionmentioning

confidence: 99%

Beamlet transform based technique for pavement image processing and classification

Ying

Salari

2009

2009 IEEE International Conference on Electro/Information Technology

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The goal of this paper is to automatically detect and classify pavement cracks using digital image processing techniques. This paper uses a pavement distress image enhancement algorithm to correct non-uniform background illumination by calculating the multiplication factors that eliminate the background lighting variations. To extract the linear features such as surface cracks from the pavement images a beamlet transform based algorithm is developed.

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Digital image processing as a tool for pavement distress evaluation

Cited by 42 publications

References 2 publications

A new approach for modelling the ingress of deleterious materials in cracked strain hardening cement-based composites

A new approach for modelling the ingress of deleterious materials in cracked strain hardening cement-based composites

Monitoring Crack Changes in Concrete Structures

Beamlet transform based technique for pavement image processing and classification

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