A hierarchical approach for low-access latency image indexing and retrieval

A major problem to be faced when efficient schemas for image indexing and retrieval are envisaged is the large workload and high complexity of underlying image-processing algorithms. The research leading to this paper focused on this problem, i.e. efficiency and scalability. A novel representation of color histograms is presented. The introduced model is based on hierarchical image adaptive color histograms. One important aspect of the envisaged hierarchic definition is that details at various levels of scale can be obtained. For fast search of similar features in large databases large sets of non-similar images are discriminated at very low computational cost using low detailed descriptions. The search is then progressively refined until only a few very similar objects or images are found and ranked using higher levels of detail. To assess the performance of the approach several experiments have been conducted. Selected results are reported.