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Please use this identifier to cite or link to this item: http://hdl.handle.net/10198/5064

Título: A segmentation approach for the identification of hazelnut cultivars
Autor: Rodrigues, Pedro
Amaral, J.S.
Santos, Alberto
Igrejas, Getúlio
Palavras-chave: Hazelnut
Segmentation
Neural networks
Issue Date: 2010
Editora: EUROSIS
Citação: Rodrigues, Pedro; Amaral, J.S.; Santos, Alberto; Igrejas, Getúlio (2010) - A segmentation approach for the identification of hazelnut cultivars. In FOODSIM 2010. Bragança. ISBN 978-90-77381-56-1. p.46-52
Resumo: The development of a methodology for cultivar discrimination and selection during on-line quality selection could be a relevant tool for certain industries that use hazelnuts as ingredients in processed food products. The aim of this work was to obtain a computer vision system that enables an automatic recognition of six hazelnuts cultivars from 3 different origins (US, Italy and Spain). To achieve this objective, an algorithm for tuning the segmentation between the hazelnut shell and crown was developed. Important morphological features that allow the correct identification of the cultivar present in an image were obtained from the segmentation process. Finally, these features were used as input data to a neural network classifier. The obtained results showed a high percentage of correct cultivar classification.
Arbitragem científica: yes
URI: http://hdl.handle.net/10198/5064
ISBN: 978-90-77381-56-1
Appears in Collections:DTQB - Publicações em Proceedings Indexadas ao ISI/Scopus

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