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dc.contributor.authorAguilera Puerto, Daniel-
dc.contributor.authorMartínez Gila, Diego Manuel-
dc.contributor.authorGámez García, Javier-
dc.contributor.authorGómez Ortega, Juan-
dc.identifier.citationPuerto, D., Gila, D., García, J., & Ortega, J. (2015). Sorting Olive Batches for the Milling Process Using Image Processing. Sensors, 15(7), 15738–15754.
dc.description.abstractThe quality of virgin olive oil obtained in the milling process is directly bound to the characteristics of the olives. Hence, the correct classification of the different incoming olive batches is crucial to reach the maximum quality of the oil. The aim of this work is to provide an automatic inspection system, based on computer vision, and to classify automatically different batches of olives entering the milling process. The classification is based on the differentiation between ground and tree olives. For this purpose, three different species have been studied (Picudo, Picual and Hojiblanco). The samples have been obtained by picking the olives directly from the tree or from the ground. The feature vector of the samples has been obtained on the basis of the olive image histograms. Moreover, different image preprocessing has been employed, and two classification techniques have been used: these are discriminant analysis and neural networks. The proposed methodology has been validated successfully, obtaining good classification results.es_ES
dc.description.sponsorshipDPI2011-27284, TEP2009-5363 and AGR-6616es_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.subjectolive classificationes_ES
dc.subjectcomputer visiones_ES
dc.subjectautomatic quality controles_ES
dc.titleSorting Olive Batches for the Milling Process Using Image Processinges_ES
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