An Efficient High-Dimensional Indexing Scheme Using a Clustering Technique for Content-Based Retrieval

Since video data, like UCC(user created contents), has recently attracted much interest, high-dimensional indexing schemes are required to satisfy userspsila requirements. However, except hybrid spill-tree, the existing high-dimensional indexing schemes are not efficient in terms of retrieval performance because they are weak in either retrieval accuracy or retrieval time. Therefore, we, in this paper, propose a new efficient high-dimensional indexing scheme to satisfy userspsila requirements by supporting the content-based retrieval of a large amount of video data. For this, we extend hybrid spill-tree with a signature-based clustering technique. In addition, we provide both an insertion algorithm and a k-NN search algorithm for our high-dimensional indexing scheme. Finally, we show that our high-dimensional indexing scheme achieves better retrieval performance than M-tree and hybrid spill-tree.