Recognition and classification of external skin damage in citrus fruits using multispectral data and morphological features

The computer vision systems currently used for the automatic inspection of citrus fruits are normally based on supervised methods that are capable of detecting defects on the surface of the fruit but are unable to discriminate between different types of defects. identifying the type of the defect af...

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Autores principales: Blasco, José, Aleixos, Nuria, Gómez-Sanchís, Juan, Moltó, Enrique
Formato: Artículo
Lenguaje:Inglés
Publicado: 2017
Acceso en línea:http://hdl.handle.net/20.500.11939/4858
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author Blasco, José
Aleixos, Nuria
Gómez-Sanchís, Juan
Moltó, Enrique
author_browse Aleixos, Nuria
Blasco, José
Gómez-Sanchís, Juan
Moltó, Enrique
author_facet Blasco, José
Aleixos, Nuria
Gómez-Sanchís, Juan
Moltó, Enrique
author_sort Blasco, José
collection ReDivia
description The computer vision systems currently used for the automatic inspection of citrus fruits are normally based on supervised methods that are capable of detecting defects on the surface of the fruit but are unable to discriminate between different types of defects. identifying the type of the defect affecting each fruit is very important in order to optimise the marketing profit and to be able to take measures to prevent such defects from occurring in the future. In this paper, we present a computer vision system that was developed for the recognition and classification of the most common external defects in citrus. in order to discriminate between 11 types of defects, images of the defects were acquired in five spectral areas, including the study of near infrared reflectance and ultraviolet induced fluorescence. The system combines spectral information about the defects with morphological estimations of them in order to classify the fruits in categories. The fruit-sorting algorithm proposed here was tested by using it to identify the defects in more than 2000 citrus fruits, including mandarins and oranges. The overall success rate reached 86%.
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spelling ReDivia48582025-04-25T14:44:48Z Recognition and classification of external skin damage in citrus fruits using multispectral data and morphological features Blasco, José Aleixos, Nuria Gómez-Sanchís, Juan Moltó, Enrique The computer vision systems currently used for the automatic inspection of citrus fruits are normally based on supervised methods that are capable of detecting defects on the surface of the fruit but are unable to discriminate between different types of defects. identifying the type of the defect affecting each fruit is very important in order to optimise the marketing profit and to be able to take measures to prevent such defects from occurring in the future. In this paper, we present a computer vision system that was developed for the recognition and classification of the most common external defects in citrus. in order to discriminate between 11 types of defects, images of the defects were acquired in five spectral areas, including the study of near infrared reflectance and ultraviolet induced fluorescence. The system combines spectral information about the defects with morphological estimations of them in order to classify the fruits in categories. The fruit-sorting algorithm proposed here was tested by using it to identify the defects in more than 2000 citrus fruits, including mandarins and oranges. The overall success rate reached 86%. 2017-06-01T10:11:11Z 2017-06-01T10:11:11Z 2009 JUN 2009 article Blasco, J., Aleixos, N., Gomez-Sanchis, J., Molto, E. (2009). Recognition and classification of external skin damage in citrus fruits using multispectral data and morphological features. Biosystems Engineering, 103(2), 137-145. 1537-5110 http://hdl.handle.net/20.500.11939/4858 10.1016/j.biosystemseng.2009.03.009 en openAccess Impreso
spellingShingle Blasco, José
Aleixos, Nuria
Gómez-Sanchís, Juan
Moltó, Enrique
Recognition and classification of external skin damage in citrus fruits using multispectral data and morphological features
title Recognition and classification of external skin damage in citrus fruits using multispectral data and morphological features
title_full Recognition and classification of external skin damage in citrus fruits using multispectral data and morphological features
title_fullStr Recognition and classification of external skin damage in citrus fruits using multispectral data and morphological features
title_full_unstemmed Recognition and classification of external skin damage in citrus fruits using multispectral data and morphological features
title_short Recognition and classification of external skin damage in citrus fruits using multispectral data and morphological features
title_sort recognition and classification of external skin damage in citrus fruits using multispectral data and morphological features
url http://hdl.handle.net/20.500.11939/4858
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AT gomezsanchisjuan recognitionandclassificationofexternalskindamageincitrusfruitsusingmultispectraldataandmorphologicalfeatures
AT moltoenrique recognitionandclassificationofexternalskindamageincitrusfruitsusingmultispectraldataandmorphologicalfeatures