Skip to main content
SpringerLink
Log in

A Dissimilarity Measure for Query by Example Retrieval

  • Conference paper
Multimedia ’99

Part of the book series: Eurographics ((EUROGRAPH))

  • 150 Accesses

Abstract

In this paper we present a method for computing the dissimilarity between a digital image and a sketch produced with a simple paint tool. Images are roughly segmented and region information (size, position, color and shape) is extracted. Multiple segmentation results are then obtained by iteratively merging pairs of regions. The dissimilarity is computed according to the region information. Experiments show that this dissimilarity measure can be used to perform similarity searches.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Philippe Aigrain, Hongjiang Zhang, Dragutin Petkovic, Content-Based Representation and Retrieval of Visual Media: A State-of-the-Art Review, Multimedia Tools and Applications, No. 3, pp. 179–202, 1996

    Article  Google Scholar 

  2. Venkat N. Guivada, Vijay V. Raghavan, Content-Based Image Retrieval Systems, IEEE Computer, Vol. 28, No. 9, pp. 18–22, 1995

    Article  Google Scholar 

  3. Suresh K. Choubey, Vijay V. Raghavan, Generic and Fully Automatic Content-Based Image Retrieval Using Color, Pattern Recognition Letters, Vol. 18, pp. 1233–1240, 1997

    Article  Google Scholar 

  4. Anil K. Jain, Aditya Vailaya, Image Retrieval Using Color and Shape, Pattern Recognition, Vol. 29, No. 8, pp. 1233–1244, 1996

    Article  Google Scholar 

  5. D.P. Huijsmans, M.S. Lew, D. Denteneer, Quality Measures for Interactive Image Retrieval with a Performance Evaluation of Two 3x3 Texel-Based Methods, Proceedings of International Conference on Image Analysis and Processing, pp. 22–29, 1997

    Google Scholar 

  6. A. Del Bimbo, M. Mugnaini, P. Pala, F. Turco, L. Verzucoli, Image Retrieval by Color Regions, Proceedings of International Conference on Image Analysis and Processing„ pp. 181–187, 1997

    Google Scholar 

  7. Colour Image Retrieval Fitted to “Classical” Querying, José Martinez and Sylvie Guillaume, Proceedings of International Conference on Image Analysis and Processing, pp. 1521, 1997

    Google Scholar 

  8. Myron Flickner, Harpreet Sawhney, Wayne Niblack, Jonathan Ashley, Qian Huang, Byron Dom, Monika Gorkani, Jim Hafner, Denis Lee, Dragutin Petkovic, David Steele and Peter Janker, Query by Image and Video Content, the QBIC System, IEEE Computer, Vol. 28, No. 9, pp. 23–32, 1995

    Article  Google Scholar 

  9. A. Pentland, R.W. Picard and S. Sclaroff, Photobook: Content-Based Manipulation of Image Databases, International Journal of Computer Vision, Vol. 18, No. 3, pp. 233–254, 1996

    Article  Google Scholar 

  10. Alberto Del Bimbo, Pietro Pala, Visual Image Retrieval by Elastic Matching of User Sketches, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, No. 2, pp. 121–132, 1997

    Article  Google Scholar 

  11. Chad Carson, Serge Belongie, Hayit Greenspan and Jitendra Malik, Region-Based Image Querying, Workshop on Content-Based Access of Image and Video Libraries, associated with the Conference on Computer Vision and Pattern Recognition, June 20, 1997, San Juan, PUR

    Google Scholar 

  12. Patrick M. Kelly, Michael Cannon, Query by Image Example: the CANDID Approach, Los Alamos National Laboratory White Paper, 1995

    Google Scholar 

  13. Virginia E. Ogle, Michael Stonebraker, Chabot: Retrieval from a Relational Database of Images, IEEE Computer, Vol. 28, No. 9, pp. 40–48, 1995

    Article  Google Scholar 

  14. Marco La Cascia, Edoardo Ardizzone, JACOB: Just a Content-Based Query System for Video Databases, in Proc. ICASSP-96, 1996

    Google Scholar 

  15. R.W.G. Hunt, Measuring Color (second edition ), 1992, Ellis Horwood, Chichester, UK

    Google Scholar 

  16. Nikhil R. Pal, Sankar K. Pal, A Review on Image Segmentation Techniques, Pattern Recognition, Vol. 26, No. 9, pp. 1277–1294, 1993

    Article  Google Scholar 

  17. Samuel S. Wilks, Mathematical Statistics, 1962, Wiley, New York, USA

    MATH  Google Scholar 

  18. Dorin Comaniciu, Peter Meer, Robust Analysis of Feature Spaces: Color Image Segmentation, Proc IEEE Conf. on Computer Vision and Pattern Recognition (CVPR ‘97), pp. 750–755, 1997

    Google Scholar 

  19. Laurent Itti, Christof Koch and Ernst Niebur, A Model for Saliency-based Visual Attention for Rapid Scene Analysis, IEEE PAMI Vol. 20, No. 11, pp. 1254–1259, 1998

    Article  Google Scholar 

  20. Folco Banfi, Rolf Ingold, Computing Dissimilarity Between Hand-Drawn Sketches and Digitized Images, in Proceedings of VISUAL99, 3rd International Conference on Visual Information Systems, Amsterdam, 1–4 June 1999

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Informatics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg, Germany

    Folco Banfi & Rolf Ingold

Authors
  1. Folco Banfi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rolf Ingold
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. New University of Lisbon, Caparica, Portugal

    Nuno Correia

  2. University of Lisbon, Lisbon, Portugal

    Teresa Chambel

  3. MIT Media Laboratory, Cambridge, MA, USA

    Glorianna Davenport

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag/Wien

About this paper

Cite this paper

Banfi, F., Ingold, R. (2000). A Dissimilarity Measure for Query by Example Retrieval. In: Correia, N., Chambel, T., Davenport, G. (eds) Multimedia ’99. Eurographics. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6771-7_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-7091-6771-7_6

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-83437-4

  • Online ISBN: 978-3-7091-6771-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation