Food Grading/Sorting Based on Color Appearance trough Machine Vision: the Case of Fresh Cranberries

Food quality depends mostly upon external appearance and in particular upon color. The purpose of this paper is to show a non destructive method for fresh cranberries color evaluation. A fresh cranberry color scale is built-up by machine vision system. Each cranberries batch to be evaluated is first photographed. The color which appears at the surface of the cranberry is not uniform and half of the surface is hidden to the camera, so a few pictures of the fruit samples are taken out, mixing the container after each shot. The individual cranberries are segmented from the background and the mean cranberry color is computed for each cranberry. The statistical validity of this multiple replicate method is first examined by an analysis of variance-one-way. The cranberries color is converted in the CIELAB color space, which is close to human perception. Then a cranberry color scale is built-up by performing first a principal component analysis on the dataset, and then by a robust data fitting method