Articolo in rivista, 2017, ENG, 10.15379/2408-9826.2017.04.01.01

Automatic Identification of Relevant Colors in Non-Destructive Quality Evaluation of Fresh Salad Vegetables

Bernardo Pace, Dario Pietro Cavallo, Maria Cefola, Giovanni Attolico

ISPA ISSIA

Quality loss during storage is often associated to changes in relevant product colors and/or to the appearance of new pigments. Computer Vision System (CVS) for non-destructive quality evaluation often relies on human knowledge provided by operators to identify these relevant colors and their features. The approach described in this paper automatically identifies the most significant colors in unevenly colored products to evaluate their quality level. Its performance was compared with results obtained by exploiting human training. The new method improved quality evaluation and reduced the subjectivity and the inconsistency potentially induced by operators.

International Journal of Food Processing Technology 4

Keywords

Non-destructive quality evaluation, Relevant colors, Automatic identification, Iceberg head lettuce

CNR authors

Cavallo Dario Pietro, Attolico Giovanni, Pace Bernardo, Cefola Maria

CNR institutes

ISPA – Istituto di scienze delle produzioni alimentari, ISSIA – Istituto di studi sui sistemi intelligenti per l'automazione