Pseudofractal 2D Shape Recognition

  • Krzysztof Gdawiec
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6401)

Abstract

From the beginning of fractal discovery they found a great number of applications. One of those applications is fractal recognition. In this paper we present some of the weaknesses of the fractal recognition methods and how to eliminate them using the pseudofractal approach. Moreover we introduce a new recognition method of 2D shapes which uses fractal dependence graph introduced by Domaszewicz and Vaishampayan in 1995. The effectiveness of our approach is shown on two test databases.

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References

  1. 1.
    Barnsley, M.: Fractals Everywhere. Academic Press, Boston (1988)MATHGoogle Scholar
  2. 2.
    Chandran, S., Kar, S.: Retrieving Faces by the PIFS Fractal Code. In: Proceedings 6th IEEE Workshop on Applications of Computer Vision, pp. 8–12 (December 2002)Google Scholar
  3. 3.
    Domaszewicz, J., Vaishampayan, V.A.: Graph-theoretical Analysis of the Fractal Transform. In: Proceedings 1995 International Conference on Acoustics, Speech, and Signal Processing, vol. 4, pp. 2559–2562 (May 1995)Google Scholar
  4. 4.
    Erra, U.: Toward Real Time Fractal Image Compression Using Graphics Hardware. In: Bebis, G., Boyle, R., Koracin, D., Parvin, B. (eds.) ISVC 2005. LNCS, vol. 3804, pp. 723–728. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  5. 5.
    Fisher, Y.: Fractal Image Compression: Theory and Application. Springer, New York (1995)Google Scholar
  6. 6.
    Gdawiec, K.: Shape Recognition using Partitioned Iterated Function Systems. Advances in Intelligent and Soft Computing 59, 451–458 (2009)CrossRefGoogle Scholar
  7. 7.
    Iftekharuddin, K.M., Jia, W., Marsh, R.: Fractal Analysis of Tumor in Brain MR Images. Machine Vision and Applications 13, 352–362 (2003)CrossRefGoogle Scholar
  8. 8.
    Latecki, L.J., Lakamper, R., Eckhardt, T.: Shape Descriptors for Non-rigid Shapes with a Single Closed Contour. In: Proceedings IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 424–429 (June 2000)Google Scholar
  9. 9.
    Mandelbrot, B.: The Fractal Geometry of Nature. W.H. Freeman and Company, New York (1983)Google Scholar
  10. 10.
    Meng, D., Cai, X., Su, Z., Li, J.: Photorealistic Terrain Generation Method Based on Fractal Geometry Theory and Procedural Texture. In: 2nd IEEE International Conference on Computer Science and Information Technology, pp. 341–344 (2009)Google Scholar
  11. 11.
    Mozaffari, S., Faez, K., Faradji, F.: One Dimensional Fractal Coder for Online Signature Recognition. In: Proceedings of the 18th International Conference on Pattern Recognition, vol. 2, pp. 857–860 (August 2006)Google Scholar
  12. 12.
    Neil, G., Curtis, K.M.: Shape Recognition Using Fractal Geometry. Pattern Recognition 30(12), 1957–1969 (1997)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Krzysztof Gdawiec
    • 1
  1. 1.Institute of Computer ScienceUniversity of SilesiaPoland

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