Abstract

An innovative Computer Vision System (CVS) that extracts color features discriminating the qualitylevels occurring during fresh-cut radicchio storage in air or modified atmosphere packaging was proposed. It self-configures the parameters normally set by operators and completely automates thefollowing steps adapting to the specific product at hand: color-chart detection, foreground extractionand color segmentation for features extraction and selection. Results proved the average value of a* 20 over the white part and the percentage of light white with respect to the whole visible surface to be the most discriminating color features to significantly separate (P <= 0.05) the three desired quality levels(high, middle and poor) occurring during fresh-cut radicchio storage 23 (whose true value was verifiedon the base of ammonium content and human evaluated visual quality). The proposed procedure significantly simplify the CVS design and the optimization of its performance, limiting the subjective human intervention to the minimum.

Autore Pugliese

• Pace Bernardo , Cefola Maria , Attolico Giovanni

Tutti gli autori

• B. PACE; D.P. CAVALLO; M. CEFOLA; R. COLELLA; G. ATTOLICO

Titolo volume/Rivista

Innovative food science & emerging technologies

Anno di pubblicazione

2015

ISSN

1466-8564

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

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Numero di citazioni Scopus

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Ultimo Aggiornamento Citazioni

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Settori ERC

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Codici ASJC

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