Applications of Image Processing in Viticulture: A Review

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aut.conference.typePaper Published in Proceedings
aut.publication.placeAdelaide, Austraia
aut.relation.endpage538
aut.relation.pages7
aut.relation.startpage531
aut.researcherShanmuganathan, Subana
dc.contributor.authorWhalley, JL
dc.contributor.authorShanmuganathan, S
dc.contributor.editorPiantadosi, J
dc.contributor.editorAnderssen, RS
dc.contributor.editorBoland, J
dc.date.accessioned2013-12-08T19:39:41Z
dc.date.accessioned2013-12-08T19:44:30Z
dc.date.accessioned2013-12-08T20:06:22Z
dc.date.available2013-12-08T19:39:41Z
dc.date.available2013-12-08T19:44:30Z
dc.date.available2013-12-08T20:06:22Z
dc.date.copyright2013-12-01
dc.date.issued2013-12-01
dc.description.abstractThe production of high quality grapes for wine making is challenging. Significant progress has been made in the automated prediction of harvest yields from images but the analysis of images to predict the quality of the harvest has yet to be fully addressed. The quality of wine produced depends in part on the quality of the grapes harvested and therefore on the presence of disease in the vineyard. There is potential for automated early detection of disease in grape crops through the development of accurate techniques for image processing. This paper presents a review of current research and highlights some of the key challenges for geo-computation (image processing, computer vision and data mining techniques) to inform the management of vineyards and highlights the key challenges for in-field image capture and analysis. An exploration of potential applications for the knowledge generated by imaging techniques is then presented. This discussion is driven by the current interest in the effect of rapid and dramatic climate change on the production of wine and focuses on how this information might be utilized to inform the design and validation of accurate predictive models.
dc.identifier.citationMSSANZ-International Congress on Modelling and Simulation held at Adelaide Convention Centre, Adelaide, Australia, 2013-12-01to 2013-12-06, published in: 20th MSSANZ-International Congress on Modelling and Simulation (MODSIM2013), pp.531 - 538 (7)
dc.identifier.isbn978-0-9872143-3-1
dc.identifier.urihttps://hdl.handle.net/10292/6149
dc.publisherThe Modelling and Simulation Society of Australia and New Zealand Inc. (MODSIM)
dc.relation.replaceshttp://hdl.handle.net/10292/6145
dc.relation.replaces10292/6145
dc.relation.replaceshttp://hdl.handle.net/10292/6146
dc.relation.replaces10292/6146
dc.relation.urihttp://www.mssanz.org.au/modsim2013/B1/whalley.pdf
dc.rightsResponsibility for the contents of these papers rests upon the authors and not on the Modelling and Simulation Society of Australia and New Zealand Inc. Every effort has been made by the members of the editorial board and reviewers to assist the authors with improving their initial submissions when and where required.
dc.rights.accessrightsOpenAccess
dc.subjectImage processing
dc.subjectClassification
dc.subjectViticulture
dc.titleApplications of Image Processing in Viticulture: A Review
dc.typeConference Contribution
pubs.elements-id156474
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Design & Creative Technologies
pubs.organisational-data/AUT/Design & Creative Technologies/School of Computing & Mathematical Science
pubs.organisational-data/AUT/Vice Chancellor's Group
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