A New Approach to Interactive Visual Search with RBF Networks Based on Preference Modelling

  • Paweł Rotter
  • Andrzej M. J. Skulimowski
Conference paper

DOI: 10.1007/978-3-540-69731-2_82

Volume 5097 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Rotter P., Skulimowski A.M.J. (2008) A New Approach to Interactive Visual Search with RBF Networks Based on Preference Modelling. In: Rutkowski L., Tadeusiewicz R., Zadeh L.A., Zurada J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2008. ICAISC 2008. Lecture Notes in Computer Science, vol 5097. Springer, Berlin, Heidelberg

Abstract

In this paper we propose a new method for image retrieval with relevance feedback based on eliciting preferences from the decision-maker acquiring visual information from an image database. The proposed extension of the common approach to image retrieval with relevance feedback allows it to be applied to objects with non-homogenous colour and texture. This has been accomplished by the algorithms, which model user queries by an RBF neural network. As an example of application of this approach, we have used a content-based search in an atlas of species. An experimental comparison with the commonly used content-based image retrieval approach is presented.

Keywords

Content-based image retrieval relevance feedback interactive multimedia retrieval RBF networks distance-based matching preference modelling 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Paweł Rotter
    • 1
    • 2
  • Andrzej M. J. Skulimowski
    • 2
  1. 1.European Commission, DG Joint Research Centre, Institute for Prospective Technological Studies, Seville, Spain, on leave from (2) 
  2. 2.Chair of Automatic ControlAGH-University of Science and TechnologyKrakowPoland