Abstract

In recent years, segmentation with graph cuts is increasingly used for a variety of applications, such as photo/video editing, medical image processing, etc. One of the most common applications of graph cut segmentation is extracting an ob ject of interest from its background. If there is any knowledge about the ob ject shape (i.e. a shape prior), in- corporating this knowledge helps to achieve a more robust segmentation. In this paper, we show how to implement a star shape prior into graph cut segmentation. This is a generic shape prior, i.e. it is not specific to any particular ob ject, but rather applies to a wide class of ob jects, in particular to convex ob jects. Our ma jor assumption is that the center of the star shape is known, for example, it can be provided by the user. The star shape prior has an additional important benefit - it allows an inclusion of a term in the ob jective function which encourages a longer ob ject boundary. This helps to alleviate the bias of a graph cut towards shorter segmentation boundaries. In fact, we show that in many cases, with this new term we can achieve an accurate ob ject segmentation with only a single pixel, the center of the ob ject, provided by the user, which is rarely possible with standard graph cut interactive segmentation.