Texture Analysis Based Damage Detection of Ageing Infrastructural Elements
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|Title:||Texture Analysis Based Damage Detection of Ageing Infrastructural Elements||Authors:||O'Byrne, Michael
|Permanent link:||http://hdl.handle.net/10197/10428||Date:||8-Nov-2012||Online since:||2019-05-14T08:11:08Z||Abstract:||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.||Funding Details:||Irish Research Council for Science, Engineering and Technology||Type of material:||Journal Article||Publisher:||Wiley Online Library||Journal:||Computer-Aided Civil and Infrastructure Engineering||Volume:||28||Issue:||3||Start page:||162||End page:||177||Copyright (published version):||2012 Computer-Aided Civil and Infrastructure Engineering||Keywords:||Infrastructure maintenance management; Visual data; Surface damage; Custom-Weighted Iterative model; 4-Dimensional Input Space model; Receiver Operating Characteristics||DOI:||10.1111/j.1467-8667.2012.00790.x||Language:||en||Status of Item:||Peer reviewed|
|Appears in Collections:||Mechanical & Materials Engineering Research Collection|
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