Now showing 1 - 10 of 16
  • Publication
    ROC dependent event isolation method for image processing based assessment of corroded harbour structures
    The localisation and calibration of damage in a structure are often difficult, time consuming, subjective and error prone. The importance of a simple, fast and relatively inexpensive non-destructive technique (NDT) with reliable measurements is thus greatly felt. The usefulness and the efficiency of any such technique are often affected by environmental conditions. The definition of damage and the subsequent interpretation of the possible consequences due to the damage introduce subjectivity into an NDT technique and affect its performance. It is of great importance in terms of practical application to find out the efficiency of an NDT technique in a probabilistic way for various damage definitions and environmental conditions through the use of receiver operating characteristic (ROC) curves. Such variations of performance of an NDT tool can be predicted through simulation processes, and the test conditions conducive to good detections can be isolated and ranked according to their relative efficiency. This paper considers a camera based image analysis technique to identify, quantify and classify damage in structures at various levels of scale. The general method has been applied to identify the affected areas on aluminium due to pitting corrosion. The method depends on the optical contrast of the corroded region with respect to its surroundings, performs intelligent edge detection through image processing techniques and computes each affected and closed region to predict the total area of the affected part, together with its spatial distribution on a two-dimensional plane. The effects of various environmental factors on the quality of such images are simulated from an original photograph. The objectivity and the amount of available information, quantification and localisation and the extent of pitting corrosion are observed, together with the various constructed ROC curves. The method provides the engineer, the owner of the structure and the end-user of the NDT technique with a tool to assess the performance of the structure in an as-built condition and decide on the appropriateness of a certain NDT, under a given environmental condition and a certain definition of damage. Moreover, it allows the findings of the NDT results to be introduced in the decision chain and risk analysis.
      346Scopus© Citations 35
  • Publication
    A Stereo-Matching Technique for Recovering 3D Information from Underwater Inspection Imagery
    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.
    Scopus© Citations 22  778
  • Publication
    An underwater lighting and turbidity image repository for analysing the performance of image-based non-destructive techniques
    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.
      804Scopus© Citations 31
  • Publication
    Semantic Segmentation of Underwater Imagery Using Deep Networks Trained on Synthetic Imagery
    Recent breakthroughs in the computer vision community have led to the emergence of efficient deep learning techniques for end-to-end segmentation of natural scenes. Underwater imaging stands to gain from these advances, however, deep learning methods require large annotated datasets for model training and these are typically unavailable for underwater imaging applications. This paper proposes the use of photorealistic synthetic imagery for training deep models that can be applied to interpret real-world underwater imagery. To demonstrate this concept, we look at the specific problem of biofouling detection on marine structures. A contemporary deep encoder–decoder network, termed SegNet, is trained using 2500 annotated synthetic images of size 960 × 540 pixels. The images were rendered in a virtual underwater environment under a wide variety of conditions and feature biofouling of various size, shape, and colour. Each rendered image has a corresponding ground truth per-pixel label map. Once trained on the synthetic imagery, SegNet is applied to segment new real-world images. The initial segmentation is refined using an iterative support vector machine (SVM) based post-processing algorithm. The proposed approach achieves a mean Intersection over Union (IoU) of 87% and a mean accuracy of 94% when tested on 32 frames extracted from two distinct real-world subsea inspection videos. Inference takes several seconds for a typical image.
      370Scopus© Citations 42
  • Publication
    Texture Analysis Based Damage Detection of Ageing Infrastructural Elements
    To make visual data a part of quantitative assessment for infrastructure maintenance management, it is important to develop computer-aided methods that demonstrate efficient performance in the presence of variability in damage forms, lighting conditions, viewing angles, and image resolutions taking into account the luminous and chromatic complexities of visual data. This article presents a semi-automatic, enhanced texture segmentation approach to detect and classify surface damage on infrastructure elements and successfully applies them to a range of images of surface damage. The approach involves statistical analysis of spatially neighboring pixels in various color spaces by defining a feature vector that includes measures related to pixel intensity values over a specified color range and statistics derived from the Grey Level Co-occurrence Matrix calculated on a quantized grey-level scale. Parameter optimized non-linear Support Vector Machines are used to classify the feature vector. A Custom-Weighted Iterative model and a 4-Dimensional Input Space model are introduced. Receiver Operating Characteristics are employed to assess and enhance the detection efficiency under various damage conditions.
    Scopus© Citations 99  608
  • Publication
    Effects of Turbidity and Lighting on the Performance of an Image Processing based Damage Detection Technique
    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.
      270
  • Publication
    Evaluation 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.
      201
  • Publication
    ROC-based Performance Analysis and Interpretation of Image-based Damage Diagnostic Tools for Underwater Inspections
    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.
      174
  • Publication
    Protocols for Image Processing based Underwater Inspection of Infrastructure Elements
    Image processing can be an important tool for inspecting underwater infrastructure elements like bridge piers and pile wharves. Underwater inspection often relies on visual descriptions of divers who are not necessarily trained in specifics of structural degradation and the information may often be vague, prone to error or open to significant variation of interpretation. Underwater vehicles, on the other hand can be quite expensive to deal with for such inspections. Additionally, there is now significant encouragement globally towards the deployment of more offshore renewable wind turbines and wave devices and the requirement for underwater inspection can be expected to increase significantly in the coming years. While the merit of image processing based assessment of the condition of underwater structures is understood to a certain degree, there is no existing protocol on such image based methods. This paper discusses and describes an image processing protocol for underwater inspection of structures. A stereo imaging image processing method is considered in this regard and protocols are suggested for image storage, imaging, diving, and inspection. A combined underwater imaging protocol is finally presented which can be used for a variety of situations within a range of image scenes and environmental conditions affecting the imaging conditions. An example of detecting marine growth is presented of a structure in Cork Harbour, Ireland.
      259Scopus© Citations 5
  • Publication
    High dynamic range image processing for non-destructive-testing
    (Taylor & Francis, 2011-10-17) ; ;
    This paper proposes High Dynamic Range (HDR) imaging as a protocol for nondestructive-testing for the first time. HDR imaging protocol has been experimentally validated on images of pitting corrosion in this paper and has been further applied to isolate a range of image backgrounds that arise out of a number of environmental conditions. The superiority of HDR imaging over a standard imaging process has been demonstrated. The results indicate that the proposed protocol is not limited by the examples considered in this paper and can readily be applied to a number of infrastructure maintenance management related applications. The protocol complements and improves standard visual inspection techniques and expert opinions. This approach immediately lends itself to further mathematical and statistical analyses, both qualitative and quantitative.
      432Scopus© Citations 5