Vector Approximation based Indexing for High-Dimensional Multimedia Databases

Imane Daoudi, S. E. Ouatik, Abdelillah El Kharraz, Khalid Koulali Idrissi, Driss Aboutajdine · 2008

Abstract—With the proliferation of multimedia data, there is an increasing need to support the indexing and searching of high-dimensional data. In this paper, we propose an efficient indexing method for high-dimensional multimedia databases using the filtering approach, known also as vector approximation approach which supports the nearest neighbor search efficiently. Our technique called RA +-Blocks (Region Approximation Blocks) divides a high-dimensional feature vector space into compact and disjoined regions. Each region will be approximated by two bit-strings according to the RA-Blocks technique. RA +-Blocks improves the division strategy of data space compared to the RA-Blocks. From our experiment using high-dimensional feature vectors, we show that RA +-Blocks achieves better performance on the nearest neighbor search than VA-File and RA-Blocks on both uniform and real data. Index Terms—High-Dimensional space, indexing method, multimedia database, nearest neighbor (NN) search. O I.

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