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 users' requirements. However, except Hybrid Spill-Tree, the existing highdimensional 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 users' 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.