A Flexible Image Retrieval Framework

  • Raoul Pascal Pein
  • Zhongyu Lu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4489)


This paper discusses a framework for image retrieval. Most current systems are based on a single technique for feature extraction and similarity search. Each technique has its advantages and drawbacks concerning the result quality. Usually they cover one or two certain features of the image, e.g. histograms or shape information.

The proposed framework is designed to be highly flexible, even if performance may suffer. The aim is to give people a platform to implement almost any kind of retrieval issues very quickly, whether it is content based or somehing else. The second advantage of the framework is the possibility to change retrieval characteristics within the program completely. This allows users to configure the ranking process as needed.


Content-based image retrieval (CBIR) retrieval framework feature vectors query image combined retrieval improved result quality 


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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Raoul Pascal Pein
    • 1
    • 2
  • Zhongyu Lu
    • 2
  1. 1.Multimedia Systems Laboratory (MMLab), Faculty of Engineering and Computer Science, Hamburg University of Applied Sciences, Berliner Tor 7, 20099 HamburgGermany
  2. 2.Department of Informatics, School of Computing and Engineering, University of Huddersfield, Queensgate, Huddersfield HD1 3DHUnited Kingdom

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