Texture Analysis Based Damage Detection of Ageing Infrastructural Elements

DC FieldValueLanguage
dc.contributor.authorO'Byrne, Michael-
dc.contributor.authorSchoefs, Franck-
dc.contributor.authorGhosh, Bidisha-
dc.contributor.authorPakrashi, Vikram-
dc.date.accessioned2019-05-14T08:11:08Z-
dc.date.available2019-05-14T08:11:08Z-
dc.date.copyright2012 Computer-Aided Civil and Infrastructure Engineeringen_US
dc.date.issued2012-11-08-
dc.identifier.citationComputer-Aided Civil and Infrastructure Engineeringen_US
dc.identifier.issn1093-9687-
dc.identifier.urihttp://hdl.handle.net/10197/10428-
dc.description.abstractTo 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.en_US
dc.description.sponsorshipIrish Research Council for Science, Engineering and Technologyen_US
dc.language.isoenen_US
dc.publisherWiley Online Libraryen_US
dc.rightsThis is the peer reviewed version of the following article: O’Byrne, M. , Schoefs, F. , Ghosh, B. and Pakrashi, V. (2013), Texture Analysis Based Damage Detection of Ageing Infrastructural Elements. Computer‐Aided Civil and Infrastructure Engineering, 28: 162-177. doi:10.1111/j.1467-8667.2012.00790.x This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.en_US
dc.subjectInfrastructure maintenance managementen_US
dc.subjectVisual dataen_US
dc.subjectSurface damageen_US
dc.subjectCustom-Weighted Iterative modelen_US
dc.subject4-Dimensional Input Space modelen_US
dc.subjectReceiver Operating Characteristicsen_US
dc.titleTexture Analysis Based Damage Detection of Ageing Infrastructural Elementsen_US
dc.typeJournal Articleen_US
dc.internal.authorcontactothervikram.pakrashi@ucd.ieen_US
dc.statusPeer revieweden_US
dc.identifier.volume28en_US
dc.identifier.issue3en_US
dc.identifier.startpage162en_US
dc.identifier.endpage177en_US
dc.citation.otherSpecial Issue: Health Monitoring of Structuresen_US
dc.identifier.doi10.1111/j.1467-8667.2012.00790.x-
dc.neeo.contributorO'Byrne|Michael|aut|-
dc.neeo.contributorSchoefs|Franck|aut|-
dc.neeo.contributorGhosh|Bidisha|aut|-
dc.neeo.contributorPakrashi|Vikram|aut|-
dc.description.othersponsorshipCAPACITES/IXEAD Societyen_US
dc.date.updated2019-05-06T19:43:36Z-
item.fulltextWith Fulltext-
item.grantfulltextopen-
Appears in Collections:Mechanical & Materials Engineering Research Collection
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