Skip to main content
SpringerLink
Log in

A Local Structure Matching Approach for Large Image Database Retrieval

  • Conference paper
Image Analysis and Recognition (ICIAR 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3211))

Included in the following conference series:

Abstract

The combination of a local structure based shape representation and a histogram based indexing structure is proposed to fast localize objects from large database. Four novel geometric attributes are extracted from each local structure. They are invariant to translation, scaling, rotation and robust to adverse distortions and noise. The search space is pruned by means of histogram intersection and the computation cost of the query is linear to the number of input features. The matching is performed by a non-metric similarity measure with regard to significance in reconstruction of query image and discrimination of different models. The concepts proposed were tested on thousands of images. The result manifests its efficiency and effectiveness.

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. Smeulders, A.W.M., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-Based Image Retrieval at the End of the Early Years. IEEE Trans. Pattern Analysis and Machine Intelligence 22(12), 1349–1380 (2000)

    Article  Google Scholar 

  2. Eakins, J.P., Riley, K.J., Edwards, J.D.: Shape Feature Matching for Trademark Image Retrieval. In: Bakker, E.M., Lew, M., Huang, T.S., Sebe, N., Zhou, X.S. (eds.) CIVR 2003. LNCS, vol. 2728, pp. 28–38. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  3. Bimbo, A.D., Pala, P.: Visual Image Retireval by Elastic Matching of User Sketches. IEEE Trans. Pattern Analysis and Machine Intelligence 19, 121–132 (1997)

    Article  Google Scholar 

  4. Zhang, D., Lu, G.: Shape-based image retrieval using generic Fourier descriptor. Signal Processing: image communication 17, 825–848 (2002)

    Article  MathSciNet  Google Scholar 

  5. Teh, C.-H., Chin, R.T.: On image analysis by the methods of moments. IEEE Trans. Pattern Analysis and Machine Intelligence 10, 496–513 (1988)

    Article  MATH  Google Scholar 

  6. Kim, Y.S., Kim, W.Y.: Content-based trademark retrieval system using a visually salient feature. Image and Vision Computing 16, 931–939 (1998)

    Article  Google Scholar 

  7. Mokhtarian, F., Mackworth, A.K.: The Curvature Scale Space Representation: Theory, Applications and MPEG-7 Standardization. Kluwer Academic Publishers, Dordrecht (2002)

    Google Scholar 

  8. Mehrota, R., Gary, J.E.: Similar-shape retrieval in shape data management. IEEE Computer 28, 57–62 (1995)

    Google Scholar 

  9. Berretti, S., Bimbo, A.D., Pala, P.: Efficient Shape Retireval by Parts. In: Solina, F., Leonardis, A. (eds.) CAIP 1999. LNCS, vol. 1689, pp. 57–64. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  10. Biederman, I., Gu, J.: Surface versus Edge-Based Determinants of Visual Recognition. Cognitive Psychology 20, 38–64 (1988)

    Article  Google Scholar 

  11. Huet, B., Hancock, E.R.: Line Pattern Retrieval Using Relational Histograms. IEEE Trans. Pattern Analysis and Machine Intelligence 21(12), 1363–1370 (1999)

    Article  Google Scholar 

  12. Koffka, K.: Principles of Gestalt Psychology. Harcourt, Brace and Company, New York (1935)

    Google Scholar 

  13. Fisher, M., Smith-Gratto, K.: Gestalt theory: a foundation for instructional screen design. Journal of educational technology systems 27(4), 361–371 (1998-1999)

    Google Scholar 

  14. Chang, D., Dooley, L., Tuovinen, J.E.: Gestalt Theory in Visual Screen Design-A New Look at an Old Subject. In: The Seventh World Conference on Computers in Education, Copenhagen, Denmark (2001)

    Google Scholar 

  15. Huet, B., Hancock, E.R.: Relational object recognition from large structural libraries. Pattern Recognition 35, 1895–1915 (2002)

    Article  MATH  Google Scholar 

  16. Leung, M.K., Yang, Y.H.: Dynamic two-strip algorithm in curve fitting. Pattern Recognition 23(1/2), 69–79 (1990)

    Article  Google Scholar 

  17. Jain, A.K., Vailaya, A.: Shape-Based Retrieval: A Case Study with Trademark Image Databases. Pattern Recognition 31(9), 1369–1390 (1998)

    Article  Google Scholar 

  18. Kim, H., Kim, J.: Region-based shape descriptor invariant to rotation. Scale and translation, Signal Processing: Image Communication 16, 87–93 (2000)

    Article  Google Scholar 

  19. Rui, Y., Huang, T.S., Chang, S.-F.: Image Retrieval: Current Techniques, Promising Directions, and Open Issues. Journal of Visual Communication and Image Representation 10, 39–62 (1999)

    Article  Google Scholar 

  20. Jain, A.K., Duin, R.P.W., Mao, J.: Statistical Pattern Recognition: A Review. IEEE Trans. Pattern Analysis and Machine Intelligence 22(1), 4–37 (2000)

    Article  Google Scholar 

  21. Brady, M.: Criteria for representations of shape. In: Beck, J., Hope, B., Rosenfeld, A. (eds.) Human and Machine Vision, pp. 39–84. Academic Press, New York (1983)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computer Engineering, Nanyang Technological University, 639798, Singapore

    Yanling Chi & Maylor K. H. Leung

Authors
  1. Yanling Chi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Maylor K. H. Leung
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. FEUP - Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio Campilho

  2. Electrical and Computer Engineering Department, University of Waterloo,  

    Mohamed Kamel

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chi, Y., Leung, M.K.H. (2004). A Local Structure Matching Approach for Large Image Database Retrieval. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30125-7_94

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-30125-7_94

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23223-0

  • Online ISBN: 978-3-540-30125-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation