Innovative classification of dolphins using deep neural networks and GrabCut

This study aims to develop a CNN-based system for dolphins' photo-identification. Starting from 1,960 photos of dolphin fins each one labeled with the related dolphin name, we have developed a predictive model able to classify unknown fins. In particular, the system is composed by two different CNNs. The first one automatically learns how to create a mask to extract the foreground, i.e. the fin, from each original image. Then, these masks are used as starting point for the GrabCut algorithm, which creates more precise binary masks. Finally, the obtained masked images are given as input to the second CNN, which aims to recognize an unknown dolphin's fin, providing a probability for each known individual.