Vector Approximation based Indexing for High-Dimensional Multimedia Databases

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.
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Article dans une revue
Engineering Letters, 2008, 2, 16, pp.210-218
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Soumis le : lundi 3 avril 2017 - 10:35:17
Dernière modification le : mercredi 28 février 2018 - 15:20:30


  • HAL Id : hal-01500347, version 1


Imane Daoudi, Said Ouatik, Abdelillah El Kharraz, Khalid Idrissi, Driss Aboutajdine. Vector Approximation based Indexing for High-Dimensional Multimedia Databases. Engineering Letters, 2008, 2, 16, pp.210-218. 〈hal-01500347〉



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