Flaw detection in aluminium die castings using simultaneous combination of multiple views

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dc.contributor.authorPieringer, C.
dc.contributor.authorMery, D.
dc.date.accessioned2024-01-10T13:48:27Z
dc.date.available2024-01-10T13:48:27Z
dc.date.issued2010
dc.description.abstractRecently, X-rays have been adopted as the principal non-destructive testing method to identify flaws within an object that are undetectable to the naked eye. Automatic inspection using radiographic images has been made possible by incorporating image processing techniques into the process. In a previous work, we proposed a framework to detect flaws in aluminium castings using multiple views. The process consisted of flaw segmentation, matching and finally tracking the flaws along the image sequence. While the previous approach required effective segmentation and matching algorithms, this investigation focuses on a new detection approach. The proposed method combines, simultaneously, information gathered from multiple views of the scene; this does not require searching for correspondences or matching. By gathering all the projections from a 3D point, obtained from a sliding box in the 3D space, we train a classifier to learn to detect simulated flaws using all the evidence available. This paper describes our proposed method and presents its performance record in flaw detections using various classifiers. Our approach yields promising results: 94% of true positives detected with 95% sensitivity in real flaws. We conclude that simultaneously combining information from different points of view is a robust approach to flaw identification.
dc.description.funderFondecyt
dc.description.funderAnillos, Chile
dc.format.extent5 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1784/insi.2010.52.10.548
dc.identifier.eissn1754-4904
dc.identifier.issn1354-2575
dc.identifier.urihttps://doi.org/10.1784/insi.2010.52.10.548
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/79366
dc.identifier.wosidWOS:000282408800005
dc.information.autorucIngeniería;Mery D;S/I;102382
dc.issue.numero10
dc.language.isoen
dc.nota.accesoSin adjunto
dc.pagina.final552
dc.pagina.inicio548
dc.publisherBRITISH INST NON-DESTRUCTIVE TESTING
dc.revistaINSIGHT
dc.rightsregistro bibliográfico
dc.subjectAutomated inspection
dc.subjectflaw detection
dc.subjectsaliency
dc.subjectcomputer vision
dc.subjectmultiple views
dc.subject.ods11 Sustainable Cities and Communities
dc.subject.odspa11 Ciudades y comunidades sostenibles
dc.titleFlaw detection in aluminium die castings using simultaneous combination of multiple views
dc.typeartículo
dc.volumen52
sipa.codpersvinculados102382
sipa.indexWOS
sipa.indexScopus
sipa.trazabilidadCarga SIPA;09-01-2024
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