Please use this identifier to cite or link to this item: http://dspace2020.uniten.edu.my:8080/handle/123456789/5035
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dc.contributor.authorKyaw, M.M.en_US
dc.contributor.authorAhmed, S.K.en_US
dc.contributor.authorMd Sharrif, Z.A.en_US
dc.date.accessioned2017-11-14T03:21:32Z-
dc.date.available2017-11-14T03:21:32Z-
dc.date.issued2009-
dc.description.abstractThe ability to sort agricultural produce automatically is very important. This paper addresses one way to identify agricultural produce based on their shape. The techniques used are based on support vector machines. The images of the produce are loaded into MATLAB and the features extracted using image processing techniques based on edge detection. These features are then input to a classifier; i.e., a support vector machine, for identification. A regular digital camera is used for acquiring the image, and all manipulations are performed in a MATLAB / SIMULINK environment. The results obtained are an improvement over a previous technique. ©2009 IEEE.en_US
dc.language.isoenen_US
dc.relation.ispartofProceedings of 2009 5th International Colloquium on Signal Processing and Its Applications, CSPA 2009 2009, Article number 5069203, Pages 135-139en_US
dc.titleShape-based sorting of agricultural produce using support vector machines in a MATLAB/SIMULINK environmenten_US
dc.typeConference Paperen_US
dc.identifier.doi10.1109/CSPA.2009.5069203-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.openairetypeConference Paper-
Appears in Collections:COE Scholarly Publication
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