Damage assessment on concrete surfaces using multi-spectral image analysis

Valença, Jónatas; Gonçalves, Luísa; Júlio, Eduardo

doi:10.1016/j.conbuildmat.2012.11.061

Cited by 45 publications

(17 citation statements)

References 9 publications

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“…The applicability of the thermal camera for building diagnostics and detection of energy-related building defects has been investigated by numerous authors [39][40][41][42][43][44]. The importance close-range remote sensing and using multispectral cameras for damage assessment and crack detection on buildings was emphasized by numerous researchers [45][46][47]. In the last few years, a growing number of studies have shown the great potential of hyperspectral cameras for detection and mapping cracks on buildings [48,49].…”

Section: The Assessment Methods For Condition Inspection and Identifimentioning

confidence: 99%

A Review of Emerging Technologies for an Assessment of Safety and Seismic Vulnerability and Damage Detection of Existing Masonry Structures

Stepinac

Gašparović

2020

Applied Sciences

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The construction sector has proven to be one of the slowest sectors to embrace technology—a problem that must be addressed. This problem can be quickly and efficiently addressed in certain aspects of seismic engineering: from seismic risk assessment to damage detection, as well as condition assessments existing structures before or after an earthquake. In this paper, the literature review of assessment methods and damage detection technologies for existing (mainly) masonry structures is presented. Traditional methods are briefly explained, and modern are critically discussed. Special focus is given to unmanned aerial vehicles, as well as, photogrammetry and close-range remote sensing as a technology that can complement traditional ways of assessment and give us data about a structure that is often different to obtain. Graphical interpretation of one post-earthquake case study is provided. Open challenges and opportunities of emerging technologies for faster and easier assessment of seismic safety and vulnerability are presented.

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Section: The Assessment Methods For Condition Inspection and Identifimentioning

confidence: 99%

A Review of Emerging Technologies for an Assessment of Safety and Seismic Vulnerability and Damage Detection of Existing Masonry Structures

Stepinac

Gašparović

2020

Applied Sciences

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“…The advantage of the developed method is a quite accurate localization of concrete surface damage, with a small calculation effort. Valenca et al [90] went one step further and created a powerful tool called "SurfCrete" for analyzing concrete surfaces. With this method, it is possible to classify an area into different classes, e.g., crack, biological corrosion, exposed aggregate grain or repair mortar.…”

Section: The Bayesian Classifiermentioning

confidence: 99%

Evaluation of Cracking Patterns in Cement Composites—From Basics to Advances: A Review

Szeląg

2020

Materials

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The structure and the development degree of a cracking pattern has a key impact on the durability of cement composites. This literature review focuses on the four most important aspects related to the evaluation of the surface cracking patterns, i.e., the process of formation, propagation and evolution of cracks into a branched system of cracks from the point of view of the fracture mechanics; the detection techniques of the cracking patterns on the surface of cement composites, where the tools of computer image analysis are the most used; parameters which can quantify the development degree and morphology of the cracks system; and also the influence of a cracking pattern on the functional features of cement composites. The studies described so far indicate the necessity of continuous development of this research area, because the knowledge of key relationships between the cracking patterns and functional properties of a cement composite is necessary to estimate the degree of material degradation. Researchers agree that the works carried out in the field of evaluation of the cracking patterns, to a large extent, contributes to the development of non-destructive testing methods in the field of cement composites technology.

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“…Subsequently, template matching and morphological operations can be performed to identify damaged regions [4]. A multispectral image analysis approach was presented by Valença et al [12] to evaluate concrete damage and delineate the deteriorated zones in an automatic manner.…”

Section: Introductionmentioning

confidence: 99%

Automatic Detection of Concrete Spalling Using Piecewise Linear Stochastic Gradient Descent Logistic Regression and Image Texture Analysis

2019

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Recognition of spalling on surface of concrete wall is crucial in building condition survey. Early detection of this form of defect can help to develop cost-effective rehabilitation methods for maintenance agencies. This study develops a method for automatic detection of spalled areas. The proposed approach includes image texture computation for image feature extraction and a piecewise linear stochastic gradient descent logistic regression (PL-SGDLR) used for pattern recognition. Image texture obtained from statistical properties of color channels, gray-level cooccurrence matrix, and gray-level run lengths is used as features to characterize surface condition of concrete wall. Based on these extracted features, PL-SGDLR is employed to categorize image samples into two classes of “nonspall” (negative class) and “spall” (positive class). Notably, PL-SGDLR is an extension of the standard logistic regression within which a linear decision surface is replaced by a piecewise linear one. This improvement can enhance the capability of logistic regression in dealing with spall detection as a complex pattern classification problem. Experiments with 1240 collected image samples show that PL-SGDLR can help to deliver a good detection accuracy (classification accuracy rate = 90.24%). To ease the model implementation, the PL-SGDLR program has been developed and compiled in MATLAB and Visual C# .NET. Thus, the proposed PL-SGDLR can be an effective tool for maintenance agencies during periodic survey of buildings.

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Damage assessment on concrete surfaces using multi-spectral image analysis

Cited by 45 publications

References 9 publications

A Review of Emerging Technologies for an Assessment of Safety and Seismic Vulnerability and Damage Detection of Existing Masonry Structures

A Review of Emerging Technologies for an Assessment of Safety and Seismic Vulnerability and Damage Detection of Existing Masonry Structures

Evaluation of Cracking Patterns in Cement Composites—From Basics to Advances: A Review

Automatic Detection of Concrete Spalling Using Piecewise Linear Stochastic Gradient Descent Logistic Regression and Image Texture Analysis

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