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dc.contributor.authorDeng, Jeremiah D.en_NZ
dc.date.available2011-04-07T03:06:21Z
dc.date.copyright2009-04en_NZ
dc.identifier.citationDeng, J. D. (2009). Automatic sapstain detection in processed timber through image feature analysis (Information Science Discussion Papers Series No. 2009/04). University of Otago. Retrieved from http://hdl.handle.net/10523/1065en
dc.identifier.urihttp://hdl.handle.net/10523/1065
dc.description.abstractSapstain is considered a defect that must be removed from processed wood. So far, research in automatic wood inspection systems has been mostly limited to dealing with knots. In this paper, we extract a number of colour and texture features from wood pictures. These features are then assessed using machine learning techniques via feature selection, visualization, and finally classification. Apart from average colour and colour opponents, texture features are also found to be useful in classifying sapstain. This implies a significant modification to the domain understanding that sapstain is mainly a discolourization effect. Preliminary results are presented, with satisfactory classification performance using only a few selected features. It is promising that a real world wood inspection system with the functionality of sapstain detection can be developed.en_NZ
dc.format.mimetypeapplication/pdf
dc.publisherUniversity of Otagoen_NZ
dc.relation.ispartofseriesInformation Science Discussion Papers Seriesen_NZ
dc.subject.lcshQA76 Computer softwareen_NZ
dc.titleAutomatic sapstain detection in processed timber through image feature analysisen_NZ
dc.typeDiscussion Paperen_NZ
dc.description.versionUnpublisheden_NZ
otago.bitstream.pages10en_NZ
otago.date.accession2009-04-29 02:50:48en_NZ
otago.schoolInformation Scienceen_NZ
otago.openaccessOpen
otago.place.publicationDunedin, New Zealanden_NZ
dc.identifier.eprints819en_NZ
otago.school.eprintsKnowledge, Intelligence & Web Informatics Laboratoryen_NZ
otago.school.eprintsInformation Scienceen_NZ
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otago.relation.number2009/04en_NZ
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