Features for Image Retrieval: A Quantitative Comparison

  • Thomas Deselaers
  • Daniel Keysers
  • Hermann Ney
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3175)


In this paper, different well-known features for image retrieval are quantitatively compared and their correlation is analyzed. We compare the features for two different image retrieval tasks (color photographs and medical radiographs) and a clear difference in performance is observed, which can be used as a basis for an appropriate choice of features. In the past a systematic analysis of image retrieval systems or features was often difficult because different studies usually used different data sets and no common performance measures were established.


Local Feature Multidimensional Scaling Image Retrieval Query Image Color Histogram 
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 2004

Authors and Affiliations

  • Thomas Deselaers
    • 1
  • Daniel Keysers
    • 1
  • Hermann Ney
    • 1
  1. 1.Lehrstuhl für Informatik VI – Computer Science DepartmentRWTH Aachen UniversityAachenGermany

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