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dc.date.accessioned 2011-02-07T13:48:41Z
dc.date.available 2011-02-07T03:00:00Z
dc.date.issued 1992
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/1466
dc.description.abstract This paper discusses a system which uses machine vision algorithms for the detection of tubes in an extremely "noisy" industrial environment . The heart of the algorithm consists of sampling of the image in predefined sparse bands perpendicular to the likely orientation of the tubes followed by the application of a normalized correlation as a detection filter over these bands. After assigning a reliability factor to each local maxima of the correlation function, these points are then mapped to the Hough space to determine the equations of the midlines of the tubes. Given these equations, the number of tubes, and any positional anomalies are reported. en
dc.format.extent 483-494 es
dc.language en es
dc.title AGUILA: an automatic tube detection system en
dc.type Objeto de conferencia es
sedici.creator.person Safar, Félix G. es
sedici.creator.person Mohtadi, Omid es
sedici.creator.person Sanz, Jorge L. C. es
sedici.subject.materias Ingeniería es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Facultad de Ingeniería es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution 4.0 International (CC BY 4.0)
sedici.rights.uri http://creativecommons.org/licenses/by/4.0/
sedici.date.exposure 1992-04-20
sedici.relation.event International Society for Photo Optical Engineering (SPIE) es
sedici.description.peerReview peer-review es
sedici2003.identifier ARG-UNLP-DIS-0000000965 es


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Creative Commons Attribution 4.0 International (CC BY 4.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution 4.0 International (CC BY 4.0)