The fish freshness was evaluated using machine vision technique through color changes of eyes and gills
of farmed and wild gilthead sea bream (Sparus aurata), being employed lightness (L), redness (a), yellowness
(b), chroma (c), and total color difference (DE) parameters during fish ice storage. A digital color
imaging system, calibrated to provide accurate CIELAB color measurements, was employed to record the
visual characteristics of eyes and gills. The region of interest was automatically selected using a computer
program developed in MATLAB software. L, b, and DE of eyes increased with storage time, while c
decreased. The a parameter of fish eyes did not show clear a trend with storage time. The L, b, and
DE of fish gills increased with storage time, but a and c decreased. Regression analysis and artificial neural
networks approaches were used to correlate the eyes and gills color parameters with the time of storage
and a strong correlation was found between color parameters and storage day. Gills color changes
were more precise than those found for eyes in order to evaluate the fish freshness. However, the gills
cover should be removed for taking the images and thus, the method is destructive and time-consuming.
Therefore, the color parameters of fish eyes can be used as a green, low cost and easy method for fast and
on-line assessing of fish freshness in food industry.