Sorting Olive Batches for the Milling Process Using Image Processing

Sensors

Daniel Aguilera Puerto¹  Diego Manuel Martínez Gila²  Javier Gámez Garc໚²  Juan Gómez Ortega² 

[1] ANDALTEC, Plastic Technological Center, Martos, Jaén 23600, Spain; E-Mail:;Group of Robotics, Automation and Computer Vision, University of Jaén, Agrifood Campus of International Excellence (ceiA3), Jaén 23071, Spain; E-Mails:

关键词: olive classification;    computer vision;    automatic quality control;   

DOI  :  10.3390/s150715738

来源: mdpi

【 摘 要 】

The 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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.