As digital images are progressing into the mainstream of information systems, managing and manipulating them as images becomes an important issue to be resolved before we can take full advantage of their information content. To achieve content-based image indexing and retrieval, there are active research efforts in developing techniques to utilize visual features. On the other hand, without an effective indexing scheme, any visual content based image retrieval approach will lose its effectiveness as the number of features increases. This paper presents our initial work in developing an efficient indexing scheme using artificial neural network, which focuses on eliminating unlikely candidates rather than pin-pointing the targets directly. Experiment results in retrieving images using this scheme from a prototype visual database system are given.
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