Development of a machine for the automatic sorting of pomegranate (Punica granatum) arils based on computer vision

The pomegranate is a fruit with excellent organoleptic and nutritional properties, but the fact that it is difficult to peel affects its commercialisation and decreases its potential consumption. One solution is to market the arils of pomegranate in a ready-to-eat form. However, after the peeling pr...

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Main Authors: Blasco, José, Cubero, Sergio, Gómez-Sanchís, Juan, Mira, P., Moltó, Enrique
Format: Artículo
Language:Inglés
Published: 2017
Online Access:http://hdl.handle.net/20.500.11939/4870
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author Blasco, José
Cubero, Sergio
Gómez-Sanchís, Juan
Mira, P.
Moltó, Enrique
author_browse Blasco, José
Cubero, Sergio
Gómez-Sanchís, Juan
Mira, P.
Moltó, Enrique
author_facet Blasco, José
Cubero, Sergio
Gómez-Sanchís, Juan
Mira, P.
Moltó, Enrique
author_sort Blasco, José
collection ReDivia
description The pomegranate is a fruit with excellent organoleptic and nutritional properties, but the fact that it is difficult to peel affects its commercialisation and decreases its potential consumption. One solution is to market the arils of pomegranate in a ready-to-eat form. However, after the peeling process, unwanted material, such as internal membranes and defective arils, is extracted together with good arils and must be removed on the packing line because the presence of such material shortens the shelf life of the product or deteriorates its appearance. For different reasons, the commercial sorting machines that are currently available for similar commodities (cherries, nuts, rice, etc.) are not capable of handling and sorting pomegranate arils, thus making it necessary to build specific equipment. This work describes the development of a computer vision-based machine to inspect the raw material coming from the extraction process and classify it in four categories. The machine is capable of detecting and removing unwanted material and sorting the arils by colour. The prototype is composed of three units, which are designed to singulate the objects to allow them be inspected individually and sorted. The inspection unit relies on a computer vision system. Two image segmentation methods were tested: one uses a threshold on the R/G ratio and the other is a more complex approach based on Bayesian Linear Discriminant Analysis (LDA) in the RGB space. Both methods offered an average success rate of 90% on a validation set, the former being more intuitive for the operators, as well as faster and easier to implement, and for these reasons it was included in the prototype. Subsequently, the complete machine was tested in industry by working in real conditions throughout a whole pomegranate season, in which it automatically sorted more than nine tons of arils.
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spelling ReDivia48702025-04-25T14:44:48Z Development of a machine for the automatic sorting of pomegranate (Punica granatum) arils based on computer vision Blasco, José Cubero, Sergio Gómez-Sanchís, Juan Mira, P. Moltó, Enrique The pomegranate is a fruit with excellent organoleptic and nutritional properties, but the fact that it is difficult to peel affects its commercialisation and decreases its potential consumption. One solution is to market the arils of pomegranate in a ready-to-eat form. However, after the peeling process, unwanted material, such as internal membranes and defective arils, is extracted together with good arils and must be removed on the packing line because the presence of such material shortens the shelf life of the product or deteriorates its appearance. For different reasons, the commercial sorting machines that are currently available for similar commodities (cherries, nuts, rice, etc.) are not capable of handling and sorting pomegranate arils, thus making it necessary to build specific equipment. This work describes the development of a computer vision-based machine to inspect the raw material coming from the extraction process and classify it in four categories. The machine is capable of detecting and removing unwanted material and sorting the arils by colour. The prototype is composed of three units, which are designed to singulate the objects to allow them be inspected individually and sorted. The inspection unit relies on a computer vision system. Two image segmentation methods were tested: one uses a threshold on the R/G ratio and the other is a more complex approach based on Bayesian Linear Discriminant Analysis (LDA) in the RGB space. Both methods offered an average success rate of 90% on a validation set, the former being more intuitive for the operators, as well as faster and easier to implement, and for these reasons it was included in the prototype. Subsequently, the complete machine was tested in industry by working in real conditions throughout a whole pomegranate season, in which it automatically sorted more than nine tons of arils. 2017-06-01T10:11:13Z 2017-06-01T10:11:13Z 2009 JAN 2009 article Blasco, J., Cubero, S., Gomez-Sanchis, J., Mira, P., Moltó, E. (2009). Development of a machine for the automatic sorting of pomegranate (Punica granatum), arils based on computer vision. Journal of Food Engineering, 90(1), 27-34. 0260-8774 http://hdl.handle.net/20.500.11939/4870 10.1016/j.jfoodeng.2008.05.035 en openAccess Impreso
spellingShingle Blasco, José
Cubero, Sergio
Gómez-Sanchís, Juan
Mira, P.
Moltó, Enrique
Development of a machine for the automatic sorting of pomegranate (Punica granatum) arils based on computer vision
title Development of a machine for the automatic sorting of pomegranate (Punica granatum) arils based on computer vision
title_full Development of a machine for the automatic sorting of pomegranate (Punica granatum) arils based on computer vision
title_fullStr Development of a machine for the automatic sorting of pomegranate (Punica granatum) arils based on computer vision
title_full_unstemmed Development of a machine for the automatic sorting of pomegranate (Punica granatum) arils based on computer vision
title_short Development of a machine for the automatic sorting of pomegranate (Punica granatum) arils based on computer vision
title_sort development of a machine for the automatic sorting of pomegranate punica granatum arils based on computer vision
url http://hdl.handle.net/20.500.11939/4870
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