Mapping perceptual texture similarity for image retrieval

Abstract

Images are being produced and made available in ever increasing numbers; but how can we find images "like this one" that are of interest to us? Many different systems have been developed which offer content-based image retrieval (CBIR), using low-level features such as colour, texture and shape; but how can the retrieval performance of such systems be measured? We have produced a perceptually-derived ranking of similar images using the Brodatz textures image dataset, based on a human study, which can be used to benchmark retrieval performance. In this paper, we show how a "mental map" may be derived from individual judgements to provide a scale of psychological distance, and a visual indication of image similarity. © Springer-Verlag Berlin Heidelberg 2005.