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.
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© 2005 Springer-Verlag Berlin Heidelberg
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Payne, J.S., Stonham, J. (2005). Mapping Perceptual Texture Similarity for Image Retrieval. In: Kalviainen, H., Parkkinen, J., Kaarna, A. (eds) Image Analysis. SCIA 2005. Lecture Notes in Computer Science, vol 3540. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11499145_97
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DOI: https://doi.org/10.1007/11499145_97
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26320-3
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