Understanding the role of surfactancts is key to making interesting structured food products, like water, oil, ... This is even more the case in recent years as the emphasis is placed more on turning towards natural emulsifiers. The researchers at Nestlé are using model monodisperse foams and emulsions to investigate the properties of different surfactants. They acquire sequence of images in various modalities of microscopy, like DIC, phase contrast, ...
The goal of the project is quantify the size of the round droplets as a function of time in sequence of images. The student has to designed algorithms, which are enough robust to a large variety of image modalities and adaptive to the various visual aspects of the droplet. The program will be implement as a plugin of ImageJ and experiment with researchers of Nestlé.
This project is in collaboration with Nestlé Research Center (CRN), Lausanne.