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Full Description
Inspection is crucial to the management of ageing infrastructure. Visual information on structures is regularly collected but very little work exists on its organised and quantitative analysis, even though image processing can significantly enhance these inspection processes and transfer real financial and safety benefits to the managers, owners and users. Additionally, new opportunities exist in the fast evolving sectors of wind and wave energy to add value to image-based inspection techniques.
This book is a first for structural engineers and inspectors who wish to harness the full potential of cameras as an inspection tool. It is particularly directed to the inspection of offshore and marine structures and the application of image-based methods in underwater inspections. It outlines a set of best practice guidelines for obtaining imagery, then the fundamentals of image processing are covered along with several image processing techniques which can be used to assess multiple damage forms: crack detection, corrosion detection, and depth analysis of marine growth on offshore structures. The book provides benchmark performance measures for these techniques under various visibility conditions using an image repository which will help inspectors to envisage the effectiveness of the techniques when applied. MATLAB® scripts and access to the underwater image repository are included so readers can run these techniques themselves.
Practising engineers and managers of infrastructure assets are guided in image processing based inspection. Researchers can use this book as a primer, and it also suits advanced graduate courses in infrastructure management or on applied image processing.
Contents
Preface. 1. Introduction. 2. Inspection Methods and Image Analysis. 3. Fundamentals of Image Acquisition and Imaging Protocol. 4. Fundamentals of Image Analysis and Interpretation. 5. Crack Detection. 6. Surface Damage Protection. 7. 3D Imaging. 8. Repository and Interpretation. 9. Future Applications. 10. Conclusions. Index.
