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dc.contributor.authorGarcía Allende, Pilar Beatriz
dc.contributor.authorConde Portilla, Olga María 
dc.contributor.authorMirapeix Serrano, Jesús María 
dc.contributor.authorCobo García, Adolfo 
dc.contributor.authorLópez Higuera, José Miguel 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2013-06-21T09:06:28Z
dc.date.available2013-06-21T09:06:28Z
dc.date.issued2010-05-13
dc.identifier.issn1996-756X
dc.identifier.issn0277-786X
dc.identifier.urihttp://hdl.handle.net/10902/2484
dc.description.abstractOptical spectroscopy has been utilized in various fields of science, industry and medicine, since each substance is discernible from all others by its spectral properties. However, optical spectroscopy traditionally generates information on the bulk properties of the whole sample, and mainly in the agri-food industry some product properties result from the heterogeneity in its composition. This monitoring is considerably more challenging and can be successfully achieved by the so-called hyperspectral imaging technology, which allows the simultaneous determination of the optical spectrum and the spatial location of an object in a surface. In addition, it is a nonintrusive and non-contact technique which gives rise to a great potential for industrial applications and it does not require any particular preparation of the samples, which is a primary concern in food monitoring. This work illustrates an overview of approaches based on this technology to address different problems in agri-food and industrial sectors. The hyperspectral system was originally designed and tested for raw material on-line discrimination, which is a key factor in the input stages of many industrial sectors. The combination of the acquisition of the spectral information across transversal lines while materials are being transported on a conveyor belt, and appropriate image analyses have been successfully validated in the tobacco industry. Lastly, the use of imaging spectroscopy applied to online welding quality monitoring is discussed and compared with traditional spectroscopic approaches in this regard.es_ES
dc.format.extent13 p.es_ES
dc.language.isoenges_ES
dc.publisherSPIE Society of Photo-Optical Instrumentation Engineerses_ES
dc.rights© 2010 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.es_ES
dc.sourceProceedings of SPIE, 2010, vol. 7726, 77260Ees_ES
dc.sourceOptical Sensing and Detection, Bruselas, 2010es_ES
dc.subject.otherOptical spectroscopyes_ES
dc.subject.otherHyperspectral imaginges_ES
dc.subject.otherNon-destructive evaluationes_ES
dc.subject.otherFood analysises_ES
dc.subject.otherMaterial classificationes_ES
dc.subject.otherArc-welding monitoringes_ES
dc.titleHyperspectral imaging for diagnosis and quality control in agri-food and industrial sectorses_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.relation.publisherVersionhttp://dx.doi.org/10.1117/12.854506es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1117/12.854506
dc.type.versionpublishedVersiones_ES


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