Image Segmentation as Learning on Hypergraphs

In this paper, we propose to use hypergraphs as the model for images and pose image segmentation as a machine learning problem in which some pixels (called seeds) are labeled as the objects and background. Using the seed pixels, our method predicts the labels for all unlabeled pixels. We present the relations of the proposed method to other hypergraph based learning techniques. We give an adaptive procedure for constructing image hypergraphs and achieve promising results on a real image dataset.