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Schoefs, Franck
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Schoefs, Franck
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Schoefs, Franck
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Now showing 1 - 10 of 16
- PublicationEvaluation of bridge safety based on Weigh-in-Motion data(Civil Engineering Research Association of Ireland, 2016-08-30)
; ; ; ; ; This paper investigates various concerns, sensitivities of and correlation between the different parameters influencing the load on a bridge and its resistance to that load. The actual safety, i.e. the probability of failure, is calculated by combining the dead load, Weigh-in-Motion data based traffic load and resistance models. The usefulness of updating the developed bridge safety model using damage indicators from a Structural Health Monitoring system is also examined.133 - PublicationEvaluation of Camera Calibration Techniques for Quantifying Deterioration(Civil Engineering Research Association of Ireland, 2016-08-30)
; ; ; Imaging systems offer an efficient way of obtaining quantitative information on the health status of structural components. They hold particular value for underwater inspections as they can be easily adapted for underwater use and they enable physical information to be captured from a scene for the purpose of later analysis. In order to make the visual data a part of a quantitative assessment, it is necessary to calibrate the imaging systems so that photographed instances of damage can be expressed and measured in physically meaningful real world units, such as millimetres, which can then be used by engineers in subsequent analyses. The imaging system employed in this study is a stereo rig. It consists of two synchronised cameras that capture images of the scene from slightly different perspectives, thereby encoding depth information. This paper evaluates and compares two main approaches for calibrating such a stereo systems, namely, the classical checkerboard procedure and self-calibration based on Kruppa’s equations. Conventional checkerboard calibration must be carried out on-site by photographing a planar checkerboard pattern that is held at multiple random poses, while self-calibration can be carried out after-the-fact and relies only on the static scene acting as a constraint on the camera parameters. The performance of each approach is assessed through a set of experiments performed on controlled real-world specimens as well as on synthetic data. Results indicate that checkerboard calibration is slightly more accurate than self-calibration; however, the practical advantages of using self-calibration may outweigh this reduction in accuracy. An understanding of the advantages and limitations associated with each camera calibration allows inspectors to rationalise the use of either approach as part of their inspection regime, and it helps them to fully capitalise on the benefits of image-based methods.100 - PublicationDamage Assessment of the Built Infrastructure using Smartphones(University College Dublin, 2018-08-30)
; ; ; The use of image-processing and machine-learning algorithms for road condition monitoring has attracted considerable interest in recent years. This surge in popularity has been propelled by advances in camera technology and the emergence of state-of-the-art deep learning techniques which have allowed inspectors to obtain high-quality imagery on a consistent basis, and then use efficient techniques to recognise road defects with credibility. A wide variety of road defect detection techniques have been proposed, however, the influence that different image acquisition devices have on the accuracy of defect detection has not been studied despite being a key component. The use of smartphone cameras as an inspection tool is of particular interest as they have become ubiquitous in recent times and the built-in cameras have progressed significantly. These cameras are now capable of producing perfectly acceptable images, yet they are still not well compared against established benchmarks. In this paper, the qualities of smartphones are explored and compared against a dedicated DSLR (Digital Single-Lens Reflex) camera. An experiment was designed that involved capturing video footage of a road surface using a smartphone (Samsung Galaxy S7) and a dedicated imaging device (Canon 600D DRSL). A deep learning based crack detection method was applied to imagery from the smartphone and the DRSL cameras and the performances levels were subsequently compared. The results indicate that smartphones are a viable, low-cost method for executing quick assessments of the road integrity. The evaluation of smartphone cameras also addresses the ongoing uncertainty around the level of performance that can be achieved using cheaper sensors for quantitative purposes. Such findings provide reassurance for inspectors wishing to use their smartphones for simple monitoring tasks.115 - PublicationBayesian updating of bridge safety model(Civil Engineering Research Association of Ireland, 2016-08-30)
; ; ; This paper investigates the sensitivities of and correlation between the different parameters influencing the load on a bridge and its resistance to that load. The actual safety, i.e. the probability of failure, is calculated by combining the load and resistance models. The usefulness of updating the developed bridge safety model using damage indicators from a Structural Health Monitoring system is also examined.99 - PublicationROC-based Performance Analysis and Interpretation of Image-based Damage Diagnostic Tools for Underwater Inspections(Taylor & Francis, 2018-10-10)
; ; ; It is of practical importance for inspectors to have knowledge of the efficiency of Non-Destructive Testing (NDT) tools when applied commercially. It has become common practice to model the performance of NDT tools in a probabilistic manner in terms of Probability of Detection (PoD), Probability of False Alarm (PFA) and eventually by Receiver Operating Characteristic (ROC) Curves. Traditionally, these quantities are estimated from training data, however, there are often doubts about the validity of these estimates when the sample size is small. In the case of underwater inspections, the scarcity of good quality training data means that this scenario arises more often than not. Comprehensive studies around the on-site performance of image-based damage diagnostic tools have only recently been made possible through the availability of online resources such as the Underwater Lighting and Turbidity Image Repository (ULTIR), which contains photographs of various damages forms captured under controlled visibility conditions. This paper shows how meaningful information can be extracted from this repository and used to construct ROC curves that can be related to the on-site performance of image-based NDT methods for detecting various damage forms and under a range of environmental conditions. The ability to draw connections between image-based techniques applied in real underwater inspections with ROC curves that can be constructed on-demand provide the engineer/ inspector with a clear and systematic route for assessing the reliability of data obtained from image-based methods. As a case study, the general approach has been applied to characterise the performance of image-based techniques for identifying instances of corrosion and cracks on marine structures. A discussion around how the results can be used for further analysis is provided. This includes looking at how the results can be fed into in the decision chain and can be used for risk analysis, intervention and work scheduling, and eventually understanding the value of information.120 - PublicationEffects of Turbidity and Lighting on the Performance of an Image Processing based Damage Detection Technique(Taylor & Francis, 2014-02-10)
; ; ; Measuring the true extent of damage in a structure remains a difficult task for inspectors. For visual inspections, an accurate assessment of the damage state is often subjective in nature and prone to error, especially when an inspection is conducted in hostile surroundings or when there are challenging environmental conditions present. While incorporating some form of Non-Destructive Technique (NDT) is generally useful for the inspection process, its performance may similarly degrade in the presence of environmental conditions. It is thus of great practical importance to have a measure of the performance of an NDT for a host of varying conditions, thereby allowing the inspector to determine whether it could be successfully applied in a given situation. In this paper, a measure of the effectiveness of an NDT is probabilistically determined for various environmental conditions through the use of Receiver Operating Characteristic (ROC) curves. ROC curves offer a convenient way of characterizing and comparing the performance of an NDT under various conditions. The NDT considered in this paper is an image processing based damage detection technique which uses texture information in conjunction with Support Vector Machine (SVM) classification to identify damaged regions. The variability of this technique is evaluated for various damage forms that are subjected to two changing parameters; turbidity and lighting. There were three set levels (low, medium, high) for each parameter. The conditions that were conducive to good detection were isolated and ranked using the α-δ method as part of the ROC analysis. The technique is applied to standard dynamic range (SDR) images and high dynamic range (HDR) images in order to assess their respective sensitivities to the changing parameters.214 - PublicationA comparison of image based 3D recovery methods for underwater inspectionsOffshore structures can be subjected to millions of variable amplitude load cycles during their service life which is the primary cause of structural deterioration. Such fatigue loading is exacerbated by marine growth colonization which changes the surface roughness characteristics and increases the diameter of structural members. Having an accurate knowledge of these parameters is essential for analyzing the increased hydrodynamic forces acting on the structure. This paper addresses the issue of acquiring shape information by comparing two popular classes of image based shape recovery techniques; stereo photography and Structure from Motion (SfM). Stereo photography utilises a dual camera set-up to simultaneously photograph an object of interest from slightly different viewpoints, whilst SfM methods generally involve a single camera moving in a static scene. In this paper, these techniques are performed on a controlled shape in an underwater setting, as well as synthetic data which allows for an irregular shape typical of marine growth to be tested whilst still having knowledge of the exact geometrical shape. The results reveal that the self-calibrated stereo approach fared well at getting an appropriately scaled full metric reconstruction, whilst the SfM approach was more susceptible to breaking down.
37 - PublicationA Stereo-Matching Technique for Recovering 3D Information from Underwater Inspection Imagery(Wiley Online Library, 2018-03)
; ; ; Underwater inspections stand to gain from using stereo imaging systems to collect three-dimensional measurements. Although many stereo-matching algorithms have been devised to solve the correspondence problem, that is, find the same points in multiple images, these algorithms often perform poorly when applied to images of underwater scenes due to the poor visibility and the complex underwater light field. This article presents a new stereo-matching algorithm, called PaLPaBEL (Pyramidal Loopy Propagated BELief) that is designed to operate on challenging imagery. At its core, PaLPaBEL is a semiglobal method based on a loopy belief propagation message passing algorithm applied on a Markov random field. A pyramidal scheme is adopted that enables wide disparity ranges and high-resolution images to be handled efficiently. For performance evaluation, PaLPaBEL is applied to underwater stereo images captured under various visibility conditions in a laboratory setting, and to synthetic imagery created in a virtual underwater environment. The technique is also demonstrated on stereo images obtained from a real-world inspection. The successful results indicate that PaLPaBEL is well suited for underwater application and has value as a tool for the cost-effective inspection of marine structures.660Scopus© Citations 16 - PublicationAn underwater lighting and turbidity image repository for analysing the performance of image-based non-destructive techniques(Taylor & Francis, 2017-05-27)
; ; ; Image processing-based methods, capable of detecting and quantifying cracks, surface defects or recovering 3D shape information are increasingly being recognised as a valuable tool for inspecting underwater structures. It is of great practical importance for inspectors to know the effectiveness of such techniques when applied in conditions. This paper considers an underwater environment characterised by poor visibility chiefly governed by the lighting and turbidity levels, along with a range of geometry and damage conditions of calibrated specimens. The paper addresses the relationship between underwater visibility and the performance of image-based methods through the development and calibration of a first open-source underwater lighting and turbidity image repository (ULTIR). ULTIR contains a large collection of images of submerged specimens that have been photographed under controlled lighting and turbidity levels featuring various forms of geometry and damage. ULTIR aims to facilitate inspectors when rationalising the use of image processing methods as part of an underwater inspection campaign and to enable researchers to efficiently evaluate the performance of image-based methods under realistic operating conditions. Stakeholders in underwater infrastructure can benefit through this first large, standardised, well-annotated, and freely available database of images and associated metadata.572Scopus© Citations 20 - PublicationRegionally enhanced multiphase segmentation technique for damaged surfaces(Wiley Online Library, 2014-09-15)
; ; ; Imaging‐based damage detection techniques are increasingly being utilized alongside traditional visual inspection methods to provide owners/operators of infrastructure with an efficient source of quantitative information for ensuring their continued safe and economic operation. However, there exists scope for significant development of improved damage detection algorithms that can characterize features of interest in challenging scenes with credibility. This article presents a new regionally enhanced multiphase segmentation (REMPS) technique that is designed to detect a broad range of damage forms on the surface of civil infrastructure. The technique is successfully applied to a corroding infrastructure component in a harbour facility. REMPS integrates spatial and pixel relationships to identify, classify, and quantify the area of damaged regions to a high degree of accuracy. The image of interest is preprocessed through a contrast enhancement and color reduction scheme. Features in the image are then identified using a Sobel edge detector, followed by subsequent classification using a clustering‐based filtering technique. Finally, support vector machines are used to classify pixels which are locally supplemented onto damaged regions to improve their size and shape characteristics. The performance of REMPS in different color spaces is investigated for best detection on the basis of receiver operating characteristics curves. The superiority of REMPS over existing segmentation approaches is demonstrated, in particular when considering high dynamic range imagery. It is shown that REMPS easily extends beyond the application presented and may be considered an effective and versatile standalone segmentation technique.388Scopus© Citations 46