Adding associative meshes to the PACCO I.P. environment

  • Alberto Biancardi
  • Alain Mérigot
Poster Session C: Compression, Hardware & Software, Image Databases, Neural Networks, Object Recognition & Construction
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1311)

Abstract

The data-parallel programming model, while perfectly suited for image processing, needs to be enhanced when shifting to image analysis. Associative meshes present two valuable benefits: they are susceptible of fast hardware implementations and they can express image computations based on connected components as whole image transformations. This paper presents, by means of coding examples, how some image analysis tasks can be expressed when a data parallel programming environment is aptly extended.

Keywords

Root Node Moment Invariant Image Transformation Valuable Benefit Image Analysis Task 
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.

References

  1. 1.
    M. G. Albanesi, V. Cantoni, U Cei, M. Ferretti and M. Mosconi, Embedding Pyramids into Mesh Arrays, in H. Li and Q. F. Stout (eds.) Reconfigurable Massively Parallel Computers, Prentice-Hall, 1990.Google Scholar
  2. 2.
    A. Biancardi, and A. Rubini, Pacco — a new approach for an effective i.p. environment, Proc. 12th ICPR, IEEE Press, Los Alamos, 1994, vol. 3, pp. 395–398.Google Scholar
  3. 3.
    D. Dulac, S. Mohammadi, and A. Mérigot Implementation and evaluation of a parallel architecture using asynchronous communication, Proc. IEEE Workshop CAMP'95, IEEE Press, Los Alamos, 1995, pp. 106–111.Google Scholar
  4. 4.
    R. C. Gonzalez, and P. Wintz Digital Image Processing (2nd ed.), Addison-Wesley, Reading, 1987.Google Scholar
  5. 5.
    M. K. Hu Visual Pattern Recognition by Moment Invariants, IRE Trans. on Information Theory, Vol. 8, pp. 179–187.Google Scholar
  6. 6.
    Recommendation T.6 — Facsimile coding schemes and coding control functions for Group 4 facsimile apparatus, International Telecommunication Union, Geneva, 1988.Google Scholar
  7. 7.
    A. Mérigot, Associative Nets: A New Parallel Computing Model, Tech. Report 92-02, Institut d'Electronique Fondamentale, Université Paris Sud, 1992.Google Scholar
  8. 8.
    J.K. Ousterhout, Tcl and the Tk Toolkit, Addison-Wesley, Reading, 1994.Google Scholar
  9. 9.
    R.A. Peters, A New Algorithm for Image Noise Reduction Using Mathematical Morphology, IEEE Trans. on Image Processing, vol. 4, no. 5, May 1995, pp. 554–567.CrossRefGoogle Scholar
  10. 10.
    K. Preston Jr. and M. J. B. Duff, Modern Cellular Automata, Plenum Press, New York, 1984.Google Scholar
  11. 11.
    J. Serra, Image Analysis and Mathematical Morphology, Academic Press, New York, 1982.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Alberto Biancardi
    • 1
  • Alain Mérigot
    • 2
  1. 1.Università di Pavia, DISPaviaItaly
  2. 2.Université de Paris-Sud, IEFOrsay CedexFrance

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