Manifold-ranking Based Image Retrieval Using Natural Neighbor

The manifold-ranking based method is widely used in semi-supervised learning, and its performance is closely related to the structure of the constructed graph. In this paper, we propose a novel graph structure named natural neighbor graph and an algorithm to construct it. We apply the new graph structure into the framework of manifold-ranking based image retrieval. The greatest superiority over k-NN based method is that the free parameter k need not to be explicitly specified any more. We have shown that the manifold ranking algorithm based on our proposed graph structure performs better than k-NN graph. Experiments demonstrate that the proposed algorithm outperforms the state-of-the-art algorithms.