Skip to main content
SpringerLink
Log in

Extraction of discriminant features from image fractal encoding

  • Perception, Vision and Robotics
  • Conference paper
  • First Online:
AI*IA 97: Advances in Artificial Intelligence (AI*IA 1997)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1321))

Included in the following conference series:

Abstract

In this paper we face the problem of finding characteristic information about. images of different objects, showing that the fractal encoding based on Iterated Function Systems, besides allowing very high compression rates, can be successfully applied also for capturing discriminatory features that can be exploited for non-fractalimage classification. An original feature extraction algorithm was developed and applied to encode the hand-written digits data set. Then, different learning algorithms were applied and their performances were compared both to those obtained using a general purpose fractal encoder (enc by Fisher and to the work done in the StatLog project on the same data set.

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

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. ECLiPSe3.5 Extensions User Manual. ECRC GmbH, 1995.

    Google Scholar 

  2. R. Anand, K. Mehrotra, C. K. Mohan, and S. Ranka. Analyzing images containing multiple sparse pattern with neural networks. In Proc. of IJCAI-91, Sidney, Australia, 1991.

    Google Scholar 

  3. M. Barnsley. Fractals Everywhere. Academic Press, San Diego, 1988.

    Google Scholar 

  4. M. Barnsley and S. Demko. Iterated function systems and the global construction of fractals. In The Proceedings of the Royal Society of London, volume A399, pages 343–275, 1985.

    Google Scholar 

  5. M. Barnsley and L. P. Hurd. Fractal Image Compression. AK Peters, Ltd., Wellesley, Massachusetts, 1993.

    Google Scholar 

  6. P. Besl and R. Jain. Three dimensional object recognition. ACM Computing Surveys, (17):75–154, 1985.

    Google Scholar 

  7. L. Breiman, J. Friedman, J. Ohlsen, and C. Stone. Classification and Regression Trees. Wadsworth & Brooks, Pacific Grove, CA, 1984.

    Google Scholar 

  8. G. Le Chiara and L. Saitta. Using fractals to learn image descriptions by means of artificial neural networks. In IEEE International Conference on Neural Networks, Orlando, USA, 1994.

    Google Scholar 

  9. R. Chin and C. Dyer. Model-based recognition in robot vision. ACM Computing Surveys, (18):67–108, 1986.

    Google Scholar 

  10. Y. Fisher (Ed.). Fractal Compression: Theory and Application to Digital Images. Springer Verlag, New York, 1994.

    Google Scholar 

  11. K. Falconer. Fractal Geometry, Mathematical Foundations and Applications. John Wiley & Sons Ltd., Chichester, UK, 1990.

    Google Scholar 

  12. D.E. Goldberg. Genetic Algorithms. Addison-Wesley, Readings, MA, 1989.

    Google Scholar 

  13. V. K. Govindan and A. P. Shivaprasad. Character recogniton — A review. Pattern Recognition, 23(7):671–683, 1990.

    Google Scholar 

  14. W. Grimson, Lozano-Pérez, and D. Huttenlocher. Recognition by Computer: The Role of Geometric Constraints. The MIT Press, Cambridge, MA, 1990.

    Google Scholar 

  15. D. Huttenlocher, G. Klanderman, and W. Rucklidge. Comparing images using the Hausdorff distance. IEEE Trans. Pattern Analysis and Machine Intelligence, (PAMI-15):850–863, 1993.

    Google Scholar 

  16. A. Jacquin. Image coding based on Factal theory of iterated contractive image transforms. In Proc. of SPIE, Visual Communications and and Image Processing '90, volume 1360, 1990.

    Google Scholar 

  17. B. Mandelbrot. The Fractal Geometry of Nature. Freeman & Co., San Francisco, CA, 1982.

    Google Scholar 

  18. D. Michie, D. J. Spiegelhalter, and C. C. Taylor. Machine learning, neural and statistical classification. Ellis Horwood series in artificial intelligence. Prentice Hall, 1994.

    Google Scholar 

  19. F. Neri and A. Giordana. A distributed genetic algorithm for concept learning. In Int. Conf. on Genetic Algorithms, pages 436–443, Pittsburgh, PA, 1995. Morgan Kaufmann.

    Google Scholar 

  20. D. Oliver. Fractal Vision, Put Fractals to Work for You. Sams Publishing, Indiana, USA, 1992.

    Google Scholar 

  21. A. P. Pentland. Fractal-Based Description of Natural Scenes. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-6(6):661–674, 1984.

    Google Scholar 

  22. A. Rosenfeld and A. Kak. Digital Picture Processing. Academic Press, New York, NY, 1982.

    Google Scholar 

  23. P. D. Wasserman. Neural computing. 1995.

    Google Scholar 

  24. C. J. Wu and J. S. Huang. Human face profile recognition by computer. Pattern Recognition, 23(3/4):255–259, 1990.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dipartimento di Informatica, University degli Studi di Torino, Corso Svizzera, 185-I-10149, Torino, Italy

    Matteo Baldoni, Cristina Baroglio, Davide Cavagnino & Giuseppe Lo Bello

Authors
  1. Matteo Baldoni
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Cristina Baroglio
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Davide Cavagnino
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Giuseppe Lo Bello
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Maurizio Lenzerini

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Baldoni, M., Baroglio, C., Cavagnino, D., Lo Bello, G. (1997). Extraction of discriminant features from image fractal encoding. In: Lenzerini, M. (eds) AI*IA 97: Advances in Artificial Intelligence. AI*IA 1997. Lecture Notes in Computer Science, vol 1321. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63576-9_102

Download citation

  • DOI: https://doi.org/10.1007/3-540-63576-9_102

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63576-5

  • Online ISBN: 978-3-540-69601-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation