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Agricultural produce sorting and grading using support vector machines and fuzzy logic

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dc.citedby42
dc.contributor.authorMustafa N.B.A.en_US
dc.contributor.authorAhmed S.K.en_US
dc.contributor.authorAli Z.en_US
dc.contributor.authorYit W.B.en_US
dc.contributor.authorAbidin A.A.Z.en_US
dc.contributor.authorMd Sharrif Z.A.en_US
dc.contributor.authorid57191952020en_US
dc.contributor.authorid25926812900en_US
dc.contributor.authorid25824589000en_US
dc.contributor.authorid35319056300en_US
dc.contributor.authorid25824750400en_US
dc.contributor.authorid6507195893en_US
dc.date.accessioned2023-12-29T07:53:20Z
dc.date.available2023-12-29T07:53:20Z
dc.date.issued2009
dc.description.abstractAgriculture sector was accorded a very different treatment in the Ninth Malaysia Plan (9MP) where this sector is being revitalized to become a part of the economic growth engine. The Information and Communication Technology (ICT) application is going to be implemented as a solution in improving the status of the agriculture sector. The idea of integrating ICT with agriculture sector motivates the development of an automated system for sorting and grading of agriculture produce. Currently, the grading is done based on observations and through experience. The developed system starts the grading process by capturing the fruit's image using a regular digital camera or mobile phone camera. Then, the image is transmitted to the processing level where feature extraction, classification and grading is done using MATLAB. In this paper, the focus is more on agricultural produce Sorting and Grading technique. The agricultural produce is classified based on fruit shape and size using Support Vector Machines (SVMs) and its grade is determined using Fuzzy Logic (FL) approach. The results obtained are very promising.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo5478684
dc.identifier.doi10.1109/ICSIPA.2009.5478684
dc.identifier.epage396
dc.identifier.scopus2-s2.0-77954473782
dc.identifier.spage391
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-77954473782&doi=10.1109%2fICSIPA.2009.5478684&partnerID=40&md5=4737bed92f118215697597b925d7c54e
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/30790
dc.pagecount5
dc.sourceScopus
dc.sourcetitleICSIPA09 - 2009 IEEE International Conference on Signal and Image Processing Applications, Conference Proceedings
dc.subjectAgricultural Produce
dc.subjectClassification
dc.subjectFuzzy logic
dc.subjectGrading
dc.subjectAgricultural machinery
dc.subjectAgricultural products
dc.subjectAutomation
dc.subjectCameras
dc.subjectEconomics
dc.subjectFeature extraction
dc.subjectFuzzy systems
dc.subjectGrading
dc.subjectImage processing
dc.subjectImaging systems
dc.subjectSupport vector machines
dc.subjectTelecommunication equipment
dc.subjectTelephone systems
dc.subjectAgricultural Produce
dc.subjectAgriculture sectors
dc.subjectAutomated systems
dc.subjectClassification
dc.subjectEconomic growths
dc.subjectFruit shape
dc.subjectGrading process
dc.subjectInformation and Communication Technologies
dc.subjectMalaysia
dc.subjectMobile phone cameras
dc.subjectFuzzy logic
dc.titleAgricultural produce sorting and grading using support vector machines and fuzzy logicen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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