A Scalable Approach for Content-Based Image Retrieval in Peer-to-Peer Networks,Peer-to-peer networking offers a scalable solution for sharing multimedia data across the network. With a large amount of visual data distributed among different nodes, it is an important but challenging issue to perform content-based retrieval in peer-to-peer networks. While most of the existing methods focus on indexing high dimensional visual features and have limitations of scalability, in this paper we propose a scalable approach for content-based image retrieval in peer-to-peer networks by employing the bag-of-visual-words model.

In addition, a peer-to-peer network often evolves dynamically, which makes a static codebook less effective for retrieval tasks.

Therefore, we propose a dynamic codebook updating method by optimizing the mutual information between the resultant codebook and relevance information, and the workload balance among nodes that manage different codewords.

Popular P2P file-sharing networks such as eDonkey count millions of users and tens of millions of files.

Unlike webpages which mainly consist of textual documents such as news, blog articles or forum posts, multimedia files play