International Journal of Food Processing Technology  (Volume 4 Issue 1)
 Automatic identification of relevant colors in non-destructive quality evaluation of fresh salad vegetables  International Journal of Food Processing Technology
Pages 1-5

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

Published: 26 January 2017
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.
Non-destructive quality evaluation, Relevant colors, Automatic identification, Iceberg head lettuce.