Non-Archimedean normalized fields in texture analysis tasks

  • Vladimir M. Chernov
  • Andrew V. Shabashev
Texture Analysis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1296)


A method of forming features of texture images is proposed. It is based on a new interpretation of digital image as a function defined on integer elements of algebraic numbers quadratic fields. The features are formed on the base of analysis of the image spectral characteristics associated with its metric properties in non-Archimedean metrics.


Prime Number Texture Image Real Texture Regular Texture Discrete Plane 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Lenz, R.: Group Theoretical Methods in Image Processing. Lecture Note Comp. Sci. Vol. 413. Springer, 1990Google Scholar
  2. 2.
    Liu, K., Huang, Y, S., Ching, Y. S.: Optimal matrix transform for the extraction of algebraic features from images. Int. J. Patt. Recogn. and Artifical Intell. (to appear)Google Scholar
  3. 3.
    Smith, G., Lovell, B.: Metrics for texture classification. Algorithms, Proc. Digital Image Comp.: Techniques and Appl. Brisbane (1995) 223–227Google Scholar
  4. 4.
    Ireland, K., Rosen, M.: A Classical Introduction to Modern Number Theory. Springer, 1982Google Scholar
  5. 5.
    Kac, M.: Statistical Indenpendece in Probability, Analysis and Number Theory. The Math. Ass. of America, 1959Google Scholar
  6. 6.
    Kac, M.: Probability and Related Topics in Physical Sciences. Intersci. Publ., London-New-York, 1958Google Scholar
  7. 7.
    Brodatz, P.: Textures: A Photographic Album for Artists and Designers. Reinhold. NY. 1986Google Scholar
  8. 8.
    Van der Waerden, B. L.: Algebra. 7th ed., Springer, 1966Google Scholar
  9. 9.
    Chernov, V. M.: A Metric Unified Treatment of Two-Dimensional FFT. Proceedings of the 13th International Conference on Pattern recognition. Vienna, (1996), Track B, 662–669Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Vladimir M. Chernov
    • 1
  • Andrew V. Shabashev
    • 1
  1. 1.Image Processing Systems Institute of RASIPSI RAS, SamaraRussia

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