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In-Line Sorting of Processed Fruit Using Computer Vision: Application to the Inspection of Satsuma Segments and Pomegranate Arils

In-Line Sorting of Processed Fruit Using Computer Vision: Application to the Inspection of Satsuma Segments and Pomegranate Arils

J. Blasco, N. Aleixos, S. Cubero, F. Albert, D. Lorente, J. Gómez-Sanchis
Copyright: © 2013 |Pages: 22
ISBN13: 9781466639942|ISBN10: 1466639946|EISBN13: 9781466639959
DOI: 10.4018/978-1-4666-3994-2.ch044
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MLA

Blasco, J., et al. "In-Line Sorting of Processed Fruit Using Computer Vision: Application to the Inspection of Satsuma Segments and Pomegranate Arils." Image Processing: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2013, pp. 874-895. https://doi.org/10.4018/978-1-4666-3994-2.ch044

APA

Blasco, J., Aleixos, N., Cubero, S., Albert, F., Lorente, D., & Gómez-Sanchis, J. (2013). In-Line Sorting of Processed Fruit Using Computer Vision: Application to the Inspection of Satsuma Segments and Pomegranate Arils. In I. Management Association (Ed.), Image Processing: Concepts, Methodologies, Tools, and Applications (pp. 874-895). IGI Global. https://doi.org/10.4018/978-1-4666-3994-2.ch044

Chicago

Blasco, J., et al. "In-Line Sorting of Processed Fruit Using Computer Vision: Application to the Inspection of Satsuma Segments and Pomegranate Arils." In Image Processing: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 874-895. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-3994-2.ch044

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Abstract

Nowadays, there is a growing demand for quality fruits and vegetables that are simple to prepare and consume, like minimally processed fruits. These products have to accomplish some particular characteristics to make them more attractive to the consumers, like a similar appearance and the total absence of external defects. Although recent advances in machine vision have allowed for the automatic inspection of fresh fruit and vegetables, there are no commercially available equipments for sorting of minority processed fruits, like arils of pomegranate (Punica granatum L) or segments of Satsuma mandarin (Citrus unshiu) ready to eat. This work describes a complete solution based on machine vision for the automatic inspection and classification of these fruits based on their estimated quality. The classification is based on morphological and colour features estimated from images taken in-line, and their analysis using statistical methods in order to grade the fruit into commercial categories.

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