An interactive example-driven approach to graphics recognition in engineering drawings

  • Liu Wenyin
  • Wan Zhang
  • Luo Yan
Original Paper


An interactive example-driven approach to graphics recognition in engineering drawings is proposed. The scenario is that the user first interactively provides an example of a graphic object; the system instantly learns its graphical knowledge and uses the acquired knowledge to recognize the same type of graphic objects. The proposed approach represents the graphical knowledge of an object in terms of its structural components and their syntactical relationships. We summarize four types of geometric constraints for knowledge representation, based on which we develop an algorithm for knowledge acquisition. Another algorithm for graphics recognition using the acquired graphical knowledge is also proposed, which is actually a sequential examination of these constraints. In the algorithm, we first guess the next component’s attributes (e.g., size, position and orientation) by reasoning from an earlier found component and the constraint between them, and then search for this hypothetical component in the drawing. If all of the hypothetical components are found, a graphic object of this type is recognized. For improving the system’s recognition accuracy, we develop a user feedback scheme, which can update the graphical knowledge from both positive (missing) and negative (mis-recognized) examples provided by the user for subsequent recognition. Experiments have shown that our proposed approach is both efficient and effective for recognizing various types of graphic objects in engineering drawings.


Graphics recognition Interactive graphics recognition Engineering drawings interpretation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    “”. GREC’03 Symbol Recognition Contest sample imagesGoogle Scholar
  2. 2.
    “”. The world’s largest online encyclopedia of graphic symbolsGoogle Scholar
  3. 3.
    “”. Ras2Vec 1.2, D. Libenzi, a freeware for vectorizationGoogle Scholar
  4. 4.
    Cheng, T., Khan, J., Liu, H., Yun, D.Y.Y. A symbol recognition system. In: Proceedings of the ICDAR93 (1993)Google Scholar
  5. 5.
    Cordella, L.P., Foggia, P., Genna, R., Vento, M. Prototyping structural descriptions: an inductive learning approach. In: Proceedings of the SSPR, pp. 339–348 (1998)Google Scholar
  6. 6.
    Dori D., Liu W. (1999) Sparse pixel vectorization: an algorithm and its performance evaluation. IEEE Trans PAMI. 21(3): 202–215Google Scholar
  7. 7.
    Dori D. (1989) A syntactic/geometric approach to recognition of dimensions in engineering machine drawings. CVGIP 47(3): 271–291Google Scholar
  8. 8.
    Flickner M., et al. (1995) Query by image and video content: the QBIC system. IEEE Comput. 28(9): 23–32Google Scholar
  9. 9.
    Kasturi, R., Tombre, K. (eds.) Graphics Recognition: methods and applications (Lecture Notes in Computer Science, vol. 1072, Springer) (Selected papers from First International Workshop on Graphics Recognition, August 1995) (1996)Google Scholar
  10. 10.
    Lee J.K., Kim K. (1996) Geometric reasoning for knowledge-based parametric design using graph representation. Comput. Aided Des. 28(10): 831–841CrossRefGoogle Scholar
  11. 11.
    Liu W., Dori D. (1998) A generic integrated line detection algorithm and Its object-process specification. CVIU 70(3): 420–437Google Scholar
  12. 12.
    Liu W., Dori D. (1998). Genericity in graphics recognition algorithms. In: Tombre K., Chhabra A. (eds). Graphics recognition: algorithms and systems, Lecture Notes in Computer Science, vol. 1389, Springer, Berlin Heidelberg New York, pp. 9–21Google Scholar
  13. 13.
    Liu W., Dori D. (1998) Incremental arc segmentation algorithm and its evaluation. IEEE Trans. PAMI 20(4): 424–431Google Scholar
  14. 14.
    Liu, W. Example-driven graphics recognition. In: Proceedings of the SSPR2002 (Structural, Syntactic, and Statistical Pattern Recognition, LNCS, vol. 2396), pp. 168–176 (2002)Google Scholar
  15. 15.
    Llados J., Valveny E., Sanchez G., Marti E. (2002) Symbol Recognition: Current Advances and Perspectives. LNCS, vol. 2390, pp. 104–127. Springer, Berlin Heidelberg New YorkGoogle Scholar
  16. 16.
    Muller, S., Eiceler, S., Rigoll, G. Image database retrieval of rotated objects by user sketch In: Proceedings of the IEEE Workshop on Content-Based Access of Image and Video Libraries, pp. 40–44 (1998)Google Scholar
  17. 17.
    Okazaki A., Kondo T., Mori K., Tsunekawa S., Kawamoto E. (1988) An automatic circuit diagram reader with loop-structure-based symbol recognition. IEEE Trans. PAMI 10(3): 331–341Google Scholar
  18. 18.
    Phillips I.T., Chhabra A.K. (1999) Empirical performance evaluation of graphics recognition systems. IEEE Trans. PAMI 21(9): 849–870Google Scholar
  19. 19.
    Samet H., Soffer, A. A legend-driven geographic symbol recognition system. In: Proceedings of the ICPR, pp. 350–355 (1994)Google Scholar
  20. 20.
    Schank R.C., Abelson R.P. (1977) Scripts, Plans, Goals and Understanding. Erlbaum, HillsdalezbMATHGoogle Scholar
  21. 21.
    Segen J. (1989). From features to symbols: learning relational models of shape. In: Simon J.C. (eds). From Pixels to Features. Elsevier, Amsterdaw pp. 237–248Google Scholar
  22. 22.
    Tabbone, S., Wendling, L., Tombre, K. Indexing of technical line drawings based on F-signatures. In: Proceedings of the ICDAR (2001)Google Scholar
  23. 23.
    Tombre, K. Analysis of engineering drawings: state of the art and challenges. In: Graphics Recognition: Algorithms and Systems, LNCS, vol. 1389, pp. 257–264. Springer, Berlin Heidelberg New York (1998)Google Scholar
  24. 24.
    Vaxiviere P., Tombre K. (1992) Celestin: CAD conversion of mechanical drawings. IEEE Comput. Mage 25(7): 46–54Google Scholar
  25. 25.
    Winston P.H. (1975). Learning structural descriptions from examples. In: Winston P.H. (eds). The Psychology of Computer Vision. McGraw-Hill, New York, pp. 157–209Google Scholar
  26. 26.
    Wong A.K.C., You M. (1985) Entropy and distance of random graphs with applications to structural pattern recognition. IEEE Trans. PAMI 7(5): 599–609zbMATHGoogle Scholar
  27. 27.
    Yan, L., Liu, W. Engineering drawings recognition using a case-based approach. In: Proceedings of the ICDAR, pp. 190–194 (2003)Google Scholar
  28. 28.
    Yan, L., Liu, W. An Interactive approach to graphics recognition in engineering drawings. In: Proceedings of the GREC pp. 170–181 (2003)Google Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  1. 1.Department of Computer ScienceCity University of Hong KongHong Kong SARPeople’s Republic of China

Personalised recommendations