Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/5037
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dc.contributor.authorMustafa, N.B.A.en_US
dc.contributor.authorFuad, N.A.en_US
dc.contributor.authorAhmed, S.K.en_US
dc.contributor.authorAbidin, A.A.Z.en_US
dc.contributor.authorAli, Z.en_US
dc.contributor.authorWong, B.Y.en_US
dc.contributor.authorSharrif, Z.A.Md.en_US
dc.date.accessioned2017-11-14T03:21:33Z-
dc.date.available2017-11-14T03:21:33Z-
dc.date.issued2008-
dc.description.abstractOver the last several decades, customers' lifestyles and needs have gone through tremendous changes. These changes are new challenges for the farmers whose produce has to meet the customers' demands. The ability to classify agriculture produce based on size and quality is not only going to help the farmer but also the customer. This will help the farmer to grade the fruit, the seller to price it optimally and the customer value for money. Bananas are classified according to sizes, shapes, textures, colors and taste. The process of getting the size and ripeness of a banana is done from its image using the Image Processing Toolbox in MATLAB. These features are important to determine the optimal size and ripeness. From the size, the grade and type of the banana can be determined. The percentage of ripeness can be determined by evaluating the individual pixels of the image. © 2008 IEEE.en_US
dc.language.isoenen_US
dc.relation.ispartofProceedings - International Symposium on Information Technology 2008, ITSim Volume 1, 2008, Article number 4631636en_US
dc.titleImage processing of an agriculture produce: Determination of size and ripeness of a bananaen_US
dc.typeConference Paperen_US
dc.identifier.doi10.1109/ITSIM.2008.4631636-
item.fulltextNo Fulltext-
item.grantfulltextnone-
Appears in Collections:COE Scholarly Publication
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