This research aims to propose a computer vision system procedure to study one of the most important features of ice cream, which is the melting behavior. Usually, melting behavior is studied by a gravimetric approach, giving information about the initial time of melting and the rate of melting. However, the aspect of the product during melting is also very important, and this method calculates a couple of indexes related to the shape and size retention of ice cream during the meltdown.
The advantage of using a computer vision system in the ice cream melting evaluation relies on the increased sensitivity in detecting small variations compared to the gravimetric method, and on the possibility to elaborate data related to the visual appearance of the product during meltdown. The computer vision system approach here proposed can be easily applied to other food products for which the melting rate and shape retention index are important, such as mousses and foams like whipped milk cream and egg albumin. These can lead to a better understanding of the meltdown mechanism, which is related to different factors.
