NNk Networks for Content-Based Image Retrieval

  • Daniel Heesch
  • Stefan Rüger
Conference paper

DOI: 10.1007/978-3-540-24752-4_19

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2997)
Cite this paper as:
Heesch D., Rüger S. (2004) NNk Networks for Content-Based Image Retrieval. In: McDonald S., Tait J. (eds) Advances in Information Retrieval. ECIR 2004. Lecture Notes in Computer Science, vol 2997. Springer, Berlin, Heidelberg

Abstract

This paper describes a novel interaction technique to support content-based image search in large image collections. The idea is to represent each image as a vertex in a directed graph. Given a set of image features, an arc is established between two images if there exists at least one combination of features for which one image is retrieved as the nearest neighbour of the other. Each arc is weighted by the proportion of feature combinations for which the nearest neighour relationship holds. By thus integrating the retrieval results over all possible feature combinations, the resulting network helps expose the semantic richness of images and thus provides an elegant solution to the problem of feature weighting in content-based image retrieval. We give details of the method used for network generation and describe the ways a user can interact with the structure. We also provide an analysis of the network’s topology and provide quantitative evidence for the usefulness of the technique.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Daniel Heesch
    • 1
  • Stefan Rüger
    • 1
  1. 1.Department of ComputingImperial CollegeLondonEngland

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