Concrete Crack Assessment Using Digital Image Processing and 3D Scene Reconstruction

Liu, Yu Fei; Cho, Su Jin; Spencer, Billie F.; Fan, Jian

doi:10.1061/(asce)cp.1943-5487.0000446

Cited by 126 publications

(57 citation statements)

References 33 publications

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“…After detecting the cracks using the proposed method, quantification of cracks can be done by employing existing quantification algorithms mostly based on combination of morphological operations, such as median filtering, morphological opening and closing, skeletonization, edge detection, etc. [52][53][54][55]. Though the lengths and widths of cracks are not quantified in this study, the crack widths obtained by visual inspection in Figure 16a are within 0.2 mm.…”

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confidence: 77%

Development of Image Processing for Crack Detection on Concrete Structures through Terrestrial Laser Scanning Associated with the Octree Structure

et al. 2018

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Terrestrial laser scanning (TLS) provides a rapid remote sensing technique to model 3D objects but can also be used to assess the surface condition of structures. In this study, an effective image processing technique is proposed for crack detection on images extracted from the octree structure of TLS data. To efficiently utilize TLS for the surface condition assessment of large structures, a process was constructed to compress the original scanned data based on the octree structure. The point cloud data obtained by TLS was converted into voxel data, and further converted into an octree data structure, which significantly reduced the data size but minimized the loss of resolution to detect cracks on the surface. The compressed data was then used to detect cracks on the surface using a combination of image processing algorithms. The crack detection procedure involved the following main steps: (1) classification of an image into three categories (i.e., background, structural joints and sediments, and surface) using K-means clustering according to color similarity, (2) deletion of non-crack parts on the surface using improved subtraction combined with median filtering and K-means clustering results, (3) detection of major crack objects on the surface based on Otsu’s binarization method, and (4) highlighting crack objects by morphological operations. The proposed technique was validated on a spillway wall of a concrete dam structure in South Korea. The scanned data was compressed up to 50% of the original scanned data, while showing good performance in detecting cracks with various shapes.

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confidence: 77%

Development of Image Processing for Crack Detection on Concrete Structures through Terrestrial Laser Scanning Associated with the Octree Structure

et al. 2018

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“…Sakagami [133] presented a remote nondestructive evaluation technique using infrared thermography to detect fatigue cracks and assess the structural integrity. Liu et al [134] combined the two-dimensional image processing technology and three-dimensional reconstruction method to assess the crack characteristics of concrete structures automatically to solve the hindrance in the practical implementation of traditional two-dimensional method. Wu et al [135] developed a crack defragmentation technique based on image processing techniques to improve the crack-detection accuracy in the road assessment task.…”

Section: Crack Inspection and Characterizationmentioning

confidence: 99%

A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications

2016

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In the past two decades, a significant number of innovative sensing and monitoring systems based on the machine vision-based technology have been exploited in the field of structural health monitoring (SHM). This technology has some inherent distinctive advantages such as noncontact, nondestructive, long distance, high precision, immunity to electromagnetic interference, and large-range and multiple-target monitoring. A lot of machine vision-based structural dynamic measurement and structural state inspection methods have been proposed. Real-world applications are also carried out to measure the structural physical parameters such as the displacement, strain/stress, rotation, vibration, crack, and spalling. The purpose of this review article is devoted to presenting a summary of the basic theories and practical applications of the machine vision-based technology employed in structural monitoring as well as its systematic error sources and integration with other modern sensing techniques.

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“…Morphological surface damage inspection/evaluation (color, texture, and shape) due to corrosion may be performed using visual inspection, which presents the drawback of using subjective criteria for decision-making. Digital image processing (DIP) methods are currently gathering high attention to on-site analysis of RCSs corrosion (Choi and Kim, 2005;Liu et al, 2016). Finite element method (FEM) shows that the cracking of concrete beams due to steel corrosion is caused by an increasing radial expansion of the corroded steel rebars.…”

Section: Introductionmentioning

confidence: 99%

Modeling Steel Corrosion Failure in Reinforced Concrete by Cover Crack Width 3D FEM Analysis

et al. 2020

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A new predictive 3D FEM model is proposed using the corrosion damage function by measuring the concrete cover crack width, which is a function of the free concrete cover depth, the steel rebar diameter, the mechanical properties of the concrete, and the length of the anodic zone. A significant aspect to evaluate service lifetime conditions in corroded reinforced concrete structures (RCSs) is the concrete cover crack width. Surface cracks originate due to the pressure exerted by the volume expansion of the corrosion products and oxide layer formed on the rebars. In this work, concrete cover crack width on corroded RCS is analyzed by means of finite element method allowing a corrosion damage model to be proposed. The model obtained was used to find a theoretical relationship between the dissolved steel (corrosion process) and the concrete cover crack width. The results were validated using three experimental data sets from the literature: two corrosion case studies in natural environments and one work covering accelerated corrosion in laboratory test conditions. All the beams were exposed to the simultaneous action of flexural stresses and corrosion. A good correlation was observed between the model and the experimental results, thus supporting reliability of the analytical process and validation of the proposed corrosion damage model.

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Concrete Crack Assessment Using Digital Image Processing and 3D Scene Reconstruction

Cited by 126 publications

References 33 publications

Development of Image Processing for Crack Detection on Concrete Structures through Terrestrial Laser Scanning Associated with the Octree Structure

Development of Image Processing for Crack Detection on Concrete Structures through Terrestrial Laser Scanning Associated with the Octree Structure

A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications

Modeling Steel Corrosion Failure in Reinforced Concrete by Cover Crack Width 3D FEM Analysis

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