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A computer vision framework for accurately extracting corroded areas and establishing the association between the type of corrosion and its extent and morphology

Kapsalas P., Maravelaki Pagona-Noni, Zervakis Michail, Delegou, E. T, Moropoulou, A

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URIhttp://purl.tuc.gr/dl/dias/2DD1C05C-FA8E-4E2E-865F-E51848683828-
Identifierhttp://library.tee.gr/digital/m2616/m2616_kapsalas.pdf-
Languageen-
Extent13 pagesen
TitleA computer vision framework for accurately extracting corroded areas and establishing the association between the type of corrosion and its extent and morphologyen
CreatorKapsalas P.en
CreatorMaravelaki Pagona-Nonien
CreatorΜαραβελακη Παγωναel
CreatorZervakis Michailen
CreatorΖερβακης Μιχαηλel
CreatorDelegou, E. Ten
CreatorMoropoulou, Aen
Content SummaryThe systematic analysis of corrosion damage on cultural heritage objects is an aspect of multidisciplinary interest. The application of computer-aided approaches in corrosion control has recently become a challenging issue. However, the majority of researches attain to estimate the decay presence by evaluating colour and texture alterations. This paper is geared towards investigating non-destructive detection and quantification of stone degradation by using machine vision schemes. The contribution of the current work is 4-fold. Thus, several detection schemes were developed, each handling in a different way the background inhomogeneity. Numerous statistical metrics were introduced to quantify corrosion damage. These metrics mainly consider the decay areas size, spatial distribution, shape and darkness. The potential of several monitoring modalities in determining corrosion attributes is studied, and the corroded areas’ shape features are considered in association with the cleaning and structural state that they represent. en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-11-05-
Date of Publication2010-
SubjectMorphological operationsen
SubjectBlob analysisen
SubjectShape studyen
SubjectStone decayen
SubjectBlack crust en
Bibliographic CitationP. Kapsalas, P. Maravelaki-Kalaitzaki, M. Zervakis, E. T. Delegou and A. Moropoulou, "A computer vision framework for accurately extracting corroded areas and establishing the association between the type of corrosion and its extent and morphology," presented at 8th International Symposium on the Conservation of Monuments in the Mediterranean Basin: Monument Damage Hazards & Rehabilitation Technologies, Patras, Greece, 2010.en

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