We describe a new indexing structure for general image retrieval that relies solely on a distance function giving the similarity between two images. For each image object in the database, its distance to a set of m predetermined vantage objects is calculated; the in-vector of these distances specifies a point in the in-dimensional vantage space. The database objects that are similar (in terms of the distance function) to a given query object can be determined by means of an efficient nearest-neighbor search on these points. We demonstrate the viability of our approach through experimental results obtained with two image databases, one consisting of about 5200 raster images of stamps, the other containing about 72,000 hieroglyphic polylines. (C) 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved. [References: 28]
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