Syntactic and Semantic Graphics Recognition: The Role of the Object-Process Methodology

  • Dov Dori
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1941)


Recognition of graphics is made at two levels: syntactic and semantic. Machines are already functioning at the syntactic level quite satisfactorily, but at the semantic level they still lack the intelligence and cognition humans apply while interpreting graphic symbols. Understanding and communicating the structure and behavior of complex systems through a graphic representation is effective only if it constitutes a visual formalism that assigns a definite semantics to each symbol. Object-Process Methodology (OPM) is a graphics-based visual formalism that has been applied to analyze and design systems in a variety of domains. Through a set of Object-Process Diagrams (OPDs) we specify a generic graphics recognition subsystem that is integrated into a Document Analysis System. Beside the direct value of the OPD representation, this model serves as an instance of the way OPM can be used as a concise graphic representation that unifies the structure and behavior of complex systems in general and graphics recognition systems in particular.


Graphic Symbol Unify Modeling Language Semantic Level Computer Integrate Manufacture Syntactic Level 
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.
    Firlej, M. and Hellens, D. Knowledge Elicitation: a Practical Handbook. Prentice Hall, New York, p.144, 1991.Google Scholar
  2. 2.
    Harel, D. Statecharts: a Visual Formalism for Complex Systems. Science of Computer Programming 8, pp. 231–274, 1987.zbMATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Harel, D., On Visual Formalisms. Communications of the ACM 31, 5, pp. 514–530, 1988.CrossRefMathSciNetGoogle Scholar
  4. 4.
    Harel, D., Biting the Silver Bullet: Toward a Brighter Future for System Development. Computer, pp. 8–20, Jan. 1992.Google Scholar
  5. 5.
    Wand, W. and Weber, R. An Ontological Evaluation of Systems Analysis and Design Methods. In Information System Concepts: An in-depth Analysis. E. D. Falkenberg and P. Lindgreen (Eds.). Elsevier Science Publishers B. V. (North Holland), pp. 145–172, IFIP 1989.Google Scholar
  6. 6.
    Bubenko, J. A. Jr.. Information System Methodologies-A Research Review. In T. W. Olle, H. G. Sol and A. A. Verrijn-Stuart (Eds.) Information System Design Methodologies-Improving the Practice. Elsevier Science Publishers B. V. (North Holland), IFIP, pp. 289–318, 1986.Google Scholar
  7. 8.
    D. Dori, Object-Process Analysis: Maintaining the Balance between System Structure and Behavior. Journal of Logic and Computation. 5(2) 227–249, 1995.CrossRefGoogle Scholar
  8. 9.
    D. Dori, Unifying System Structure and Behavior through Object-Process Analysis. Journal of Object-Oriented Programming, July-August, pp. 66–73, 1996.Google Scholar
  9. 10.
    D. Dori and Y. J. Dori, Object-Process Analysis of a Hypertext Organic Chemistry Studyware. Journal of Computers in Mathematics and Science Teaching, 15, 1/2, (1996),65–84.Google Scholar
  10. 11.
    D. Dori, Object-Process Analysis of Computer Integrated Manufacturing Documentation and Inspection Functions. International Journal of Computer Integrated Manufacturing, 9(5), 339–353, 1996.CrossRefGoogle Scholar
  11. 12.
    D. Meyersdorf and D. Dori, The R&D Universe and Its Feedback Cycles: an Object-Process Analysis. R&D Management, 27 (4), 333–344, 1997.Google Scholar
  12. 13.
    M. Peleg and D. Dori, Extending the Object-Process Methodology to Handle Real-Time Systems. Journal of Object-Oriented Programming, 11, 8, pp. 53–58, 1999.Google Scholar
  13. 14.
    D. Dori, Representing Pattern Recognition Embedded Systems through Object-Process Diagrams: the Case of the Machine Drawing Understanding System. Pattern Recognition Letters, 16 (4), 377–384, 1995.CrossRefGoogle Scholar
  14. 15.
    D. Dori, Arc Segmentation in the Machine Drawing Understanding Environment. IEEE Transactions of Pattern Analysis and Machine Intelligence (T-PAMI), 17 (1), 1057–1068, 1995.CrossRefGoogle Scholar
  15. 16.
    D. Dori and M. Weiss, A Scheme for 3D Object Reconstruction from Dimensioned Orthographic Views. Engineering Applications in Artificial Intelligence, 9 (1), 53–64, 1996.CrossRefGoogle Scholar
  16. 17.
    D. Dori and H. Hel-Or: Semantic Content-Based Image Retrieval Using Object-Process Diagrams. In A. Amin, D. Dori, P. Pudil and H. Freeman (Eds.) Advances in Pattern Recognition, Lecture Notes in Computer Science, Vol. 1451, 230–241, 1998.Google Scholar
  17. 18.
    Dov Dori and Liu Wenyin, Automated CAD Conversion with the Machine Drawing Understanding System: Concepts, Algorithms, and Performance. IEEE Transactions on Systems, Man, and Cybernetics, 29, 4, pp.411–416, 1999.CrossRefGoogle Scholar
  18. 19.
    D. Dori and L. Wenyin, The Sparse Pixel Vectorization Algorithm and its Performance Evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 21, 3 pp. 202–215, 1999.CrossRefGoogle Scholar
  19. 20.
    L. Wenyin and D. Dori, A Generic Integrated Line Detection Algorithm and its Object-Process Specification. Computer Vision. Image Understanding (CVIU), 70, 3, pp. 420–437, 1998.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Dov Dori
    • 1
  1. 1.Information Systems Engineering, Faculty of Industrial Engineering and ManagementTechnion, Israel Institute of TechnologyHaifaIsrael

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