Setting graph cut weights for automatic foreground extraction in wood log images

The automatic extraction of foreground objects from the background is a well known problem. Much research has been done to solve the foreground/background segmentation with graph cuts. The major challenge is to determine the weights of the graph in order to obtain a good segmentation. In this paper we address this problem with a focus on the automatic segmentation of wood logs. We introduce a new solution to get information about foreground and background. This information is used to set the weights of the graph cut method. We compare four different methods to set these weights and show that the best results are obtained with our novel method, which is based on density estimation.