Adaptive self-configuring computer vision system for quality evaluation of fresh-cut radicchio
Articolo
Data di Pubblicazione:
2015
Abstract:
An innovative Computer Vision System (CVS) that extracts color features discriminating the quality
levels 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 the
following steps adapting to the specific product at hand: color-chart detection, foreground extraction
and 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 verified
on 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.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Computer vision system; non-destructive quality evaluation; self-configuration; automatic colors and features selection; image analysis
Elenco autori:
Colella, Roberto; Cavallo, DARIO PIETRO; Attolico, Giovanni; Pace, Bernardo; Cefola, Maria
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