Mapping Perceptual Texture Similarity for Image Retrieval

  • Janet S. Payne
  • John Stonham
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3540)

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.

Keywords

Image Retrieval Query Image Retrieval Performance Similarity Scale Psychological Distance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Janet S. Payne
    • 1
  • John Stonham
    • 2
  1. 1.Centre for Applied Computing, Faculty of TechnologyBuckinghamshire Chilterns University CollegeHigh WycombeUK
  2. 2.Dept of Electronic and Computer EngineeringBrunel UniversityUxbridge

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