Task-Based User Evaluation of Content-Based Image Database Browsing Systems

  • Timo Ojala
  • Markus Koskela
  • Esa Matinmikko
  • Mika Rautiainen
  • Jorma Laaksonen
  • Erkki Oja
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3115)


This paper presents a task-based user evaluation of two content-based image database browsing systems. The performance of the two systems is compared to that of a commercial image database management program, which does not employ content-based information. Experimental results show that content-based cues improve the efficiency of the browsing considerably. Guidelines for system design are derived from the user feedback.


Image Retrieval Search Time Image Database Target Image Test User 
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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  1. 1.
    Baeza-Yates, R., Ribeiro-Neto, N.: Modern Information Retrieval. Addison Wesley, Essex (1999)Google Scholar
  2. 2.
    Card, S.K., Mackinlay, J.D., Shneiderman, B.: Readings in Information Visualization, Using Vision to Think. Morgan Kaufmann Publishers, San Francisco (1999)Google Scholar
  3. 3.
    Heesch, D., Yavlinsky, A., Rüger, S.: Performance Comparison Between Different Similarity Models for CBIR with Relevance Feedback. In: Proc. International Conference on Image and Video Retrieval. Urbana-Champaign, pp. 456–466 (2003)Google Scholar
  4. 4.
    Hull, D.: Using Statistical Testing in The Evaluation of Retrieval Experiments. In: Proc. ACM SIGIR 1993, Pittsburg, pp. 329–338 (1993)Google Scholar
  5. 5.
    Kohonen, T.: Self-Organizing Maps. Springer, Heidelberg (2001)zbMATHGoogle Scholar
  6. 6.
    Koikkalainen, P., Oja, E.: Self-organizing Hierarchical Feature Maps. In: International Joint Conference on Neural Networks, San Diego, pp. 279–284 (1990)Google Scholar
  7. 7.
    Koskela, M.: Interactive Image Retrieval using Self-Organizing Maps. PhD thesis, Laboratory of Computer and Information Science, Helsinki University of Technology (2003), available online at:
  8. 8.
    Laaksonen, J., Koskela, M., Laakso, S., Oja, E.: Self-Organizing Maps as a Relevance Feedback Technique in Content-Based Image Retrieval. Pattern Analysis and Applications 4, 140–152 (2001)zbMATHCrossRefMathSciNetGoogle Scholar
  9. 9.
    Laaksonen, J., Koskela, M., Oja, E.: PicSOM- Self-Organizing Image Retrieval with MPEG-7 Content Descriptions. IEEE Transactions on Neural Networks 13, 841–853 (2002)CrossRefGoogle Scholar
  10. 10.
    Nielsen, J.: Usability engineering. Academic Press, Boston (1993)Google Scholar
  11. 11.
    Matinmikko, E.: Image Database Browsing System. M.Sc. thesis, Department of Electrical Engineering, University of Oulu, Finland (2004)Google Scholar
  12. 12.
    Reeves, T., Hedberg, J.: Interactive Learning Systems Evaluation. Educational Technology Publications, Englewood Cliffs (2003)Google Scholar
  13. 13.
    van Rijsbergen, C.J.: Information Retrieval. Butterworths, London (1979)Google Scholar
  14. 14.
    ACDSee Photo Software 4.0 (2003),

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Timo Ojala
    • 1
  • Markus Koskela
    • 2
  • Esa Matinmikko
    • 3
  • Mika Rautiainen
    • 1
  • Jorma Laaksonen
    • 2
  • Erkki Oja
    • 2
  1. 1.MediaTeam OuluUniversity of OuluFinland
  2. 2.Laboratory of Computer and Information ScienceHelsinki University of TechnologyFinland
  3. 3.Mawell LtdFinland

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