Texprint: A New Algorithm to Discriminate Textures Structurally

  • Antoni Grau
  • Joan Climent
  • Francesc Serratosa
  • Alberto Sanfeliu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2396)


In this work a new algorithm for texture analysis is presented. Over a region with size NxN in the image, a texture print is found by means of counting the number of changes in the sign of the derivative in the gray level intensity function by rows and by columns. These two histograms (Hx and Hy) are represented as a unique string R of symbols. In order to discriminate different texture regions a distance measure on strings based on minimum-cost sequences of edit operations is computed.


Texture Image Edit Distance String Match Texture Region Similar Texture 
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.


  1. 1.
    P. Brodatz, Textures: A Photographic Album for Artist and Designers, Dover Publishing Co., New York, 1966.Google Scholar
  2. 2.
    H. Bunke and A. Sanfeliu, Syntactic and Structural Pattern Recognition Theory and Applications, Series in Computer Science, Vol. 7, World Scientific Publ., 1990.Google Scholar
  3. 3.
    J. Climent, A. Grau, J. Aranda and A. Sanfeliu, “Low Cost Architecture for Structure Measure Distance Computation”, ICPR’98, Australia, pp. 1592–1594, August 1998.Google Scholar
  4. 4.
    J. Climent, A. Grau, J. Aranda and A. Sanfeliu, “Clique-to-Clique Distance Computation Using a Specific Architecture”, SSPR’98, Sydney, Australia, pp. 405–412, August 1998.Google Scholar
  5. 5.
    R.M. Haralick, “Statistical and Structural Approaches to Texture”, Proc. of the IEEE 67, No. 5, pp. 786–804, 1979.CrossRefGoogle Scholar
  6. 6.
    H.-C. Liu and M.D. Srinath, “Classification of partial shapes using string-to-string matching”, Intell. Robots and Comput. Vision, SPIE Proc. Vol. 1002, pp. 92–98, 1989.Google Scholar
  7. 7.
    S.Y. Lu and K.S. Fu, “A Syntactic Approach to Texture Analysis”, Computer Graphics & Im. Proc, Vol. 7, No. 3, 1978.Google Scholar
  8. 8.
    T. Matsuyama, K. Saburi and M. Nagao, “A Structural Analyzer for Regularly Arranged Textures”, Computer Graphics and Image Processing, Vol. 18, pp. 259–278, 1982.CrossRefGoogle Scholar
  9. 9.
    D. Sankoff and J.B. Kruskal, eds, Time Warps, String Edit and Macromolecules: The Theory and Practice of Sequence Comparison, Addison-Wesley, Reading, MA, 1983.Google Scholar
  10. 10.
    F. Tomita and S. Tsuji, Computer Analysis of Visual Textures, Kluwer Academic Publishers, 1990.Google Scholar
  11. 11.
    W.H. Tsai and S.S. Yu, “Attributed string matching with merging for shape recognition”, IEEE Trans. Patt. Anal. Mach. Intell. 7, No. 4, pp. 453–462, 1985.CrossRefGoogle Scholar
  12. 12.
    R.A. Wagner et al., “The string-to-string correction problem”, J. Ass. Comput. Mach. 21,No l, pp. 168–173, 1974.zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Antoni Grau
    • 1
    • 2
  • Joan Climent
    • 1
    • 2
  • Francesc Serratosa
    • 1
    • 2
  • Alberto Sanfeliu
    • 3
  1. 1.Dept Automatic ControlTechnical University of Catalonia UPCBarcelonaSpain
  2. 2.Universitiy Rovira i Virgili TarragonaSpain
  3. 3.Institute for Robotics, UPC/CSICBarcelonaSpain

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