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An analysis of multi-level filtering for high dimensional image data Tam, Dominic Pok Man

Abstract

Image database systems are very useful in many applications. To design an effective image database system, high dimensional image feature vectors have to be extracted from the images automatically. Each comparison between them tends to be expensive, so sequential comparisons are usually impractical. Moreover, the. traditional multi-dimensional indexing structures are incapable of handling these high-dimensional vectors efficiently. Thus, it has been proposed to abstract lower dimensional k-D vector from the original N-D feature vector, where k

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