A neural network approach to discrimination between defects and calyces in oranges

The problem of automatic discrimination among pictures concerning either defects or calyces in oranges is approached. The method here proposed is based on a statistical analysis of the grey-levels and the shape of calyces in the pictures. Some suitable statistical indices are considered and the disc... Ausführliche Beschreibung

1. Person: Salvatore Ingrassia verfasserin
Weitere Personen: Enrico Commis verfasserin
Quelle: In Le Matematiche (01.11.1993)
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Format: Online-Artikel
Sprache: English
French
Italian
Veröffentlicht: 1993
Beschreibung: Online-Ressource
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  Creative Commons License Source: Directory of Open Access Journals (DOAJ).
Zusammenfassung: The problem of automatic discrimination among pictures concerning either defects or calyces in oranges is approached. The method here proposed is based on a statistical analysis of the grey-levels and the shape of calyces in the pictures. Some suitable statistical indices are considered and the discriminant function is designed by means of a neural network on the basis of a suitable vector representation of the images. Numerical experiments give 5 misclassifications in a set of 52 images, where only three defects have been classified as calyces.
ISSN: 0373-3505

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