An intelligent system for quality measurement of Golden Bleached raisins using two comparative machine learning algorithms

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dc.contributor.authorKarimi, Navab
dc.contributor.authorRanjbarzadeh Kondrood, Ramin
dc.contributor.authorAlizadeh, Tohid
dc.creatorNavab, Karimi
dc.date.accessioned2017-12-22T08:43:40Z
dc.date.available2017-12-22T08:43:40Z
dc.date.issued2017-09-01
dc.description.abstractAbstract In this research, an expert system is provided for measuring and recognizing the quality and purity of mixed (pure-impure) raisins using bulk raisins’ images. For this purpose, by utilizing a machine vision setup 1400 images of the raisins were captured in the several ranges of mixture (from 5 to 50%). Then, totally 146 textural features were obtained using four methods of gray-level histograms, gray level co-occurrence matrix (GLCM), gray level run-length (GLRM) matrix, and local binary pattern (LBP). Principal Components Analysis (PCA) was used in order to find the optimum features from the extracted features. Accordingly, Artificial Neural Network (ANN) and Support Vector Machine (SVM) were used for classifying the mixtures. In comparison to ANN, using top 50 features, SVM classifier had more efficient and accurate classification results (averagely 92.71%). The results of the proposed approach can be used in designing a system for purity and quality measuring of raisins.en_US
dc.identifierDOI:10.1016/j.measurement.2017.05.009
dc.identifier.citationNavab Karimi, Ramin Ranjbarzadeh Kondrood, Tohid Alizadeh, An intelligent system for quality measurement of Golden Bleached raisins using two comparative machine learning algorithms, In Measurement, Volume 107, 2017, Pages 68-76en_US
dc.identifier.issn02632241
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0263224117302877
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/3050
dc.language.isoenen_US
dc.publisherMeasurementen_US
dc.relation.ispartofMeasurement
dc.rights.license© 2017 Elsevier Ltd. All rights reserved.
dc.subjectImage processingen_US
dc.subjectGolden Bleached Raisin (GBR)en_US
dc.subjectBulk texturesen_US
dc.subjectTextural featuresen_US
dc.subjectSupport Vector Machineen_US
dc.subjectArtificial Neural Networken_US
dc.titleAn intelligent system for quality measurement of Golden Bleached raisins using two comparative machine learning algorithmsen_US
dc.typeArticleen_US
elsevier.aggregationtypeJournal
elsevier.coverdate2017-09-01
elsevier.coverdisplaydateSeptember 2017
elsevier.endingpage76
elsevier.identifier.doi10.1016/j.measurement.2017.05.009
elsevier.identifier.eid1-s2.0-S0263224117302877
elsevier.identifier.piiS0263-2241(17)30287-7
elsevier.identifier.scopusid85019130693
elsevier.openaccess0
elsevier.openaccessarticlefalse
elsevier.openarchivearticlefalse
elsevier.startingpage68
elsevier.teaserIn this research, an expert system is provided for measuring and recognizing the quality and purity of mixed (pure-impure) raisins using bulk raisins’ images. For this purpose, by utilizing a machine...
elsevier.volume107
workflow.import.sourcescience

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