Skip to main content

Intelligent Mining in Image Databases, with Applications to Satellite Imaging and to Web Search

  • Chapter

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 68))

Abstract

An important part of our knowledge is in the form of images. For example, a large amount of geophysical and environmental data comes from satellite photos, a large amount of the information stored on the Web is in the form of images, etc. It is therefore desirable to use this image information in data mining. Unfortunately, most existing data mining techniques have been designed for mining numerical data and are thus not well suited for image databases. Hence, new methods are needed for image mining. In this paper, we show how data mining can be used to find common patterns in several images.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover 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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. H. Bunke and M. Zumbuehl, “Acquisition of 2D shape models from scenes with overlapping objects using string matching”, Pattern Anal. Appl., 1999, Vol. 2, No. 1, pp. 2–9.

    Article  MATH  Google Scholar 

  2. K. J. Cios, W. Pedrycz, and R. Swiniarski, Data Mining Methods for Knowledge Discovery, Kluwer. Dordrecht, 1998.

    Book  MATH  Google Scholar 

  3. U. M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy (eds.), Advances in Knowledge Discovery and Data Mining, MIT Press, Cambridge, MA, 1996.

    Google Scholar 

  4. S. Gibson, An optimal FFT-based algorithm for mosaicing images, Master Thesis, Department of Computer Science, University of Texas at El Paso, December 1999.

    Google Scholar 

  5. X. Jiang, K. Yu, and H. Bunke, “Detection of rotational and involutional symmetries and congruity of polyhedra”, Visual Comput., 1996, Vol. 12, No. 4, pp. 193–201.

    MATH  Google Scholar 

  6. L. T. Koczy, V. Kreinovich, Y. Mendoza, H. T. Nguyen, and H. Schulte, “Towards Mathematical Foundations of Information Retrieval: Dependence of Websité s Relevance on the Number of Occurrences of a Queried Word”, Proceedings of the Joint Conferences in Information Sciences JCIS’2000}, Atlantic City, NJ, February 27-March 3, 2000 (to appear).

    Google Scholar 

  7. O. Kosheleva, L. Longpre, and R. Osegueda, “Detecting Known Non-Smooth Structures in Images: Fuzzy and Probabilistic Methods, with Applications to Medical Imaging, Non-Destructive Testing, and Detecting Text on Web Pages”, Proceedings of The Eighth International Fuzzy Systems Association World Congress IFSA’99, Taipei, Taiwan, August 1720, 1999, pp. 269–273.

    Google Scholar 

  8. V. Kreinovich, C. Quintana, and O. Fuentes. “Genetic algorithms: what fitness scaling is optimal?” Cybernetics and Systems: an International Journal, 1993, Vol. 24, No. 1, pp. 9–26.

    Article  MathSciNet  MATH  Google Scholar 

  9. J. Llados, H. Bunke, and E. Marti, “Finding rotational symmetries by cyclic string matching”, Pattern Recognit. Lett., 1997, Vol. 18, No. 14, pp. 1435–1442.

    MATH  Google Scholar 

  10. R. S. Michalski, M. Kubat, I. Bratko, and A. Bratko (eds.), Machine Learning and Data Mining: Methods and Applications, J. Wiley & Sons, New York, 1998.

    Google Scholar 

  11. H. T. Nguyen and V. Kreinovich, Applications of continuous mathematics to computer science, Kluwer, Dordrecht, 1997.

    MATH  Google Scholar 

  12. L. Polkowski et al. (eds.), Rough sets in knowledge discovery 1. Methodology and applications, Physica-Verlag: Heidelberg, 1998 (Studies in Fuzziness and Soft Comput. Vol. 18).

    Google Scholar 

  13. B. S. Reddy and B. N. Chatterji, “An 11-.1-Based Technique for Translation, Rotation, and Scale-Invariant Image Registration,” IEEE Transactions on Image Processing, 1996, Vol. 5, No. 8, pp. 1266–1271.

    Article  Google Scholar 

  14. K. Shearer, H. Bunke, S. Venkatesh, and D. Kieronska, “Efficient graph matching for video indexing”, in: J.-M. Jolion et al. (eds.), Graph based representations in pattern recognition. Workshop, GbR ’97, Lyon, France, April 17–18, 1997, Wien: Springer: Wien, Comput. Suppl. 1998, Vol. 12, pp. 53–62.

    Google Scholar 

  15. Y.-Q. Zhang and A. Kandel, Compensatory Genetic Fuzzy Neural Networks and Their Applications, World Scientific, Singapore, 1998.

    MATH  Google Scholar 

  16. N. Zhong, A. Skowron, and S. Ohsuga (eds.), New directions in rough sets, data mining, and granular-soft computing, Proc. of the 7th international workshop, RSFDGrC ’99, Yamaguchi, Japan, November 9–11, 1999. Proceedings, Springer-Verlag Lecture Notes in Artificial Intelligence, Vol. 1711, Berlin, 1999

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2001 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Gibson, S., Kreinovich, V., Longpre, L., Penn, B., Starks, S.A. (2001). Intelligent Mining in Image Databases, with Applications to Satellite Imaging and to Web Search. In: Kandel, A., Last, M., Bunke, H. (eds) Data Mining and Computational Intelligence. Studies in Fuzziness and Soft Computing, vol 68. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1825-3_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-7908-1825-3_12

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2484-1

  • Online ISBN: 978-3-7908-1825-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics