Syntactic and Structural Methods in Document Image Analysis

  • Alberto Sanfeliu

Abstract

We survey applications of syntactic and structural pattern recognition (SSPR) methods to the field of document image analysis, analyze the strengths and weakness of these methods for document image analysis, and discuss other complementary techniques.

Keywords

Remotely Sense Zucker 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [AHPE72]
    A. V. Aho and T. G. Peterson, “A minimum distance error-correcting parser for context-free languages,” SIAM J. Computing4, pp. 305–312, 1972.CrossRefMathSciNetGoogle Scholar
  2. [AHUL73]
    A. V. Aho and J. D. Ullman, The theory of parsing translation and compiling. Prentice-Hall, Englewood Cliffs, NJ, 1973.Google Scholar
  3. [BA78]
    B. S. Baker, “Tree transducers and tree languages.,” Inf. Control37, pp. 241–266, 1978.CrossRefMATHGoogle Scholar
  4. [BE78]
    D. A. Bell, “Decision trees, tables and lattices,” In B. G. Batchelor (ed.), Pattern Recognition, Plenum Press, 1978.Google Scholar
  5. [BU90]
    H. Bunke, “String matching for structural pattern recognition,” In H. Bunke & A. Sanfeliu (eds), Syntactic and structural pattern recognition: theory and applications, World Scientific, Singapore, pp. 119–144, 1990.Google Scholar
  6. [BUSA90]
    H. Bunke and A. Sanfeliu (eds), Syntactic and structural pattern recognition: theory and applications. 1990.MATHGoogle Scholar
  7. [ENRR87]
    H. Ehrig, M. Nagl, G. Rozenberg, and A. Rosenfeld (eds.), Graph grammars and their application to computer science. Lecture Notes Computer Science 297. Springer-Verlag, Berlin, 1987.MATHGoogle Scholar
  8. [FIN79]
    N. V. Findler (ed,), Associative networks: the representation and use of knowledge by computers. Academic Press, New York, 1979.Google Scholar
  9. [FU82]
    K. S. Fu, Syntactic pattern recognition and applications. Prentice-Hall, Englewood Cliffs, NJ, 1982.MATHGoogle Scholar
  10. [FU83]
    K. S. Fu, “A step towards unification of syntactic and statistical pattern recognition,” IEEE Trans. PAMI 5, pp. 200–205, 1983.MATHGoogle Scholar
  11. [GOTH78]
    R. C. Gonzalez and M. G. Thomason, Syntactic pattern recognition. Addison-Wesley, Reading, MA, 1978.MATHGoogle Scholar
  12. [GHR80]
    S. L. Graham, M. A. Harrison, and W. L. Ruzzo, “An improved context- free recognizer,” ACM Trans. Program Lang, and Syst., pp. 415–449, 1980.Google Scholar
  13. [HAR83]
    R. M. Haralick, “An interpretation for probabilistic relaxation,” Comp. Vision, Graphics and Image Processing 22, 1983.Google Scholar
  14. [HOUL79]
    J. E. Hopcroft and J. D. Ullman, Introduction to automata theory, languages and computation. Addison-Wesley, Reading, MA, 1979.MATHGoogle Scholar
  15. [HUZU83]
    R. Hummel and S. Zucker, On the foundations of relaxation labeling processes. IEEE Trans. PAMI 5, pp. 267–287, 1983.CrossRefMATHGoogle Scholar
  16. [LEV66]
    V. I. Levenshtein, “Binary codes capable of correcting deletions, insertions and reversals,” Sov. Phys. Dokl. 10 (8), pp. 707–710, 1966.MathSciNetGoogle Scholar
  17. [LU84]
    S. Y Lu, “A tree matching algorithm based on node splitting and merging,” IEEE Trans. PAMI 6, pp. 249–256, 1984.CrossRefMATHGoogle Scholar
  18. [LUFU78]
    S. Y. Lu and K. S. Fu, “Error-correcting tree automata for syntactic pattern recognition,” IEEE Trans. Computers 27, pp. 1040–1053, 1978.CrossRefMATHMathSciNetGoogle Scholar
  19. [LYON74]
    G. Lyon, “Syntax-directed least-errors analysis for context-free languages: a practical approach,” CACM 17, pp. 3–14, 1974.MATHGoogle Scholar
  20. [MIC86]
    L. Miclet, Structural methods in pattern recognition. North-Oxford Academic, 1986.MATHGoogle Scholar
  21. [MIN75]
    M. Minsky, “A framework for representing knowledge,” In P. Winston (ed), The psychology of computer vision, McGraw-Hill, New York, 1975.Google Scholar
  22. [NIL80]
    N. J. Nilsson, Principles of artificial intelligence. Tioga, Palo Alto, California, 1980.MATHGoogle Scholar
  23. [PAV77]
    T. Pavlidis, Structural pattern recognition. Springer Series Electrophysics Springer-Verlag, Berlin, 1977.MATHGoogle Scholar
  24. [PEA84]
    J. Pearl, Heuristics: intelligent search strategies for computer problem solving. Addison-Wesley, Reading, MA, 1984.Google Scholar
  25. [PEA88]
    J. Pearl, Probabilistic reasoning in intelligent systems: networks of plausible inference. Morgan Kaufmann, 1988.Google Scholar
  26. [ROS 79]
    A. Rosenfeld, Picture languages: formal models for picture recognition. Academic Press, New York, 1979.MATHGoogle Scholar
  27. [RHZ76]
    A. Rosenfeld, R. A. Hummel, and S. W. Zucker, “Scene labeling by relaxation operations,” IEEE Trans. SMC 6, pp. 420–443, 1976.MATHMathSciNetGoogle Scholar
  28. [SA90]
    A. Sanfeliu, “Matching tree structures,” In H. Bunke and A. Sanfeliu (eds), Syntactic and structural pattern recognition: theory and applications, World Scientific, Singapore, pp. 145–178, 1990.Google Scholar
  29. [SAFU83]
    A. Sanfeliu and K. S. Fu, “A distance measure between attributed relational graphs for pattern recognition,” IEEE Trans. SMC 13, No. 3, pp. 353–362, 1983.MATHGoogle Scholar
  30. [SHHA90]
    L. G. Shapiro and R. M. Haralick, “Matching relational structures using discrete relaxation,” In H. Bunke & A. Sanfeliu (eds), Syntactic and structural pattern recognition: theory and applications, World Scientific, Singapore, pp. 179–196, 1990.Google Scholar
  31. [TAI79]
    K. C. Tai, “The tree to tree correction problem,” J. ACM 26, pp. 422–433, 1979.CrossRefMATHMathSciNetGoogle Scholar
  32. [TAN88]
    E. Tanaka, “Efficient computing algorithms for the Tai metric,” Int’l J. Pattern Recognition and Artificial Intelligence, 1988.Google Scholar
  33. [TAN90]
    E. Tanaka, “Parsing and error-correcting parsing for string grammars,” In H. Bunke & A. Sanfeliu (eds), Syntactic and structural pattern recognition: theory and applications, World Scientific, Singapore, pp. 55–84, 1990.Google Scholar
  34. [TAFU82]
    E. Tanaka and K. S. Fu, “Error correcting parsers for formal languages,” IEEE Trans. Comp. 31, pp. 327–328, 1982.CrossRefMATHMathSciNetGoogle Scholar
  35. [TSFU85]
    W. H. Tsai and K. S. Fu, “Attributed string matching with merging for shape recognition,” IEEE Trans. PAMI 7, pp. 453–462, 1985.CrossRefGoogle Scholar
  36. [WAL75]
    D. Waltz, “Understanding line drawings of scenes with shadows,” In P. Winston (ed), The psychology of computer vision, McGraw-Hill, New York, pp. 19–91, 1975.Google Scholar
  37. [YOFU76]
    K. C. You and K. S. Fu, “An approach to design of a linear binary classifier,” Proc. Symp. of Machine Processing of Remotely Sensed Data, Purdue Univ., 1976.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Alberto Sanfeliu
    • 1
  1. 1.Instituto de CibernéticaUniversidad Politécnica de CataluñaBarcelonaSpain

Personalised recommendations