Visual inspection of glass bottlenecks by multiple-view analysis

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dc.contributor.authorCarrasco, Miguel
dc.contributor.authorPizarro, Luis
dc.contributor.authorMery, Domingo
dc.date.accessioned2024-01-10T13:44:11Z
dc.date.available2024-01-10T13:44:11Z
dc.date.issued2010
dc.description.abstractThe narrow structure of bottlenecks poses a very challenging problem for automated visual inspection systems and surprisingly, this issue has received little attention in literature. Bottleneck inspection is highly relevant to the fabrication of glass bottles, e.g., for the wine and beer industry. Defects in glass bottles can arise in various situations such as an incomplete reaction in a batch, batch contaminants and interactions of the melted material among others. This paper presents an inspection approach that utilises geometry of multiple views along with a rich set of feature descriptors to discriminate real flaws from false alarms in uncalibrated images of glass bottlenecks. The proposed method is based on an automatic multiple view inspection (AMVI) technique for the automatic detection of flaws. This technique involves an initial step that extracts numerous segmented regions from a set of views of the object under inspection. These regions are subsequently classified either as real flaws or as false alarms. The classification process considers that image noise and false alarms occur as random events in different views while real flaws induce geometric and featural relations in the views where they appear. Therefore, by analysing such relations it is possible to successfully localise real flaws and to discard a large number of false alarms. An important characteristic of the proposed methodology is the complete lack of camera calibration which makes our method very suitable for applications where camera calibration is difficult or expensive to carry out. Our inspection system achieves a true positive rate of 99.1% and a false positive rate of 0.9%.
dc.description.funderNational Commission for Scientific and Technological Research (CONICYT)
dc.description.funderGerman Academic Exchange Service (DAAD)
dc.fechaingreso.objetodigital2024-05-09
dc.format.extent17 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1080/0951192X.2010.500676
dc.identifier.eissn1362-3052
dc.identifier.issn0951-192X
dc.identifier.urihttps://doi.org/10.1080/0951192X.2010.500676
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/78859
dc.identifier.wosidWOS:000282129700005
dc.information.autorucIngeniería;Mery D;S/I;102382
dc.issue.numero10
dc.language.isoen
dc.nota.accesocontenido parcial
dc.pagina.final941
dc.pagina.inicio925
dc.publisherTAYLOR & FRANCIS LTD
dc.revistaINTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
dc.rightsacceso restringido
dc.subjectautomated visual inspection
dc.subjectflaw detection
dc.subjectmultiple views
dc.subjectuncalibrated images
dc.subjectglass bottlenecks
dc.subjectPATTERN-RECOGNITION
dc.subjectNEURAL-NETWORKS
dc.subjectFEATURES
dc.subjectDEFECTS
dc.subject.ods11 Sustainable Cities and Communities
dc.subject.odspa11 Ciudades y comunidades sostenibles
dc.titleVisual inspection of glass bottlenecks by multiple-view analysis
dc.typeartículo
dc.volumen23
sipa.codpersvinculados102382
sipa.indexWOS
sipa.indexScopus
sipa.trazabilidadCarga SIPA;09-01-2024
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