<title>Linear mapping functions for high-dimensional indexing in image databases</title>

Abstract

The problem of indexing high-dimensional data has received renewed interest because of its necessity in emerging multimedia databases. The limitations of traditional tree-based indexing and the dimensionality curse is well known. We have proposed a hierarchical indexing structure based on linear mapping functions, which is not tree-based, and not necessarily balanced. At each level of the hierarchy, a linear mapping function is used to distribute the data among buckets. The feasibility and the performance of the indexing structure is dependent on finding appropriate mapping functions for any given data set. In this paper we present the approach taken in arriving at a few classes of mapping functions. We have given a heuristic algorithm to determine the choice of the most appropriate mapping function for a given data set. The results of experiments with real life data are presented and they indicate that the proposed indexing structure with linear mapping functions is indeed practical.