A Vectorization System for Architecture Engineering Drawings

  • Feng Su
  • Jiqiang Song
  • Shijie Cai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3926)


This paper presents a vectorization system for architecture engineering drawings. The system employs the line-symbol-text vectorization workflow to recognize graphic objects in the order of increasing characteristic complexity and progressively simplify the drawing image by removing recognized objects from it. Various recognition algorithms for basic graphic types have been developed and efficient interactive recognition methods are proposed as complements to automatic processing. Based on dimension recognition and analysis, the system reconstructs the literal dimension for vectorization results, which yields optimized vector data for CAD applications.


Grid Line Graphic Object Text Block Engineering Drawing Dimension Frame 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Tombre, K.: Analysis of engineering drawings: state of the art and challenges. In: Chhabra, A.K., Tombre, K. (eds.) GREC 1997. LNCS, vol. 1389, pp. 257–264. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  2. 2.
    Dori, D., Liu, W.: Automated CAD conversion with the machine drawing understanding system: Concepts, algorithm, and performance. IEEE Trans. on System, Man, and Cybernetics-part A: System and Humans 29(4), 411–416 (1999)CrossRefGoogle Scholar
  3. 3.
    Doermann, D.S.: An introduction to vectorization and segmentation. In: Chhabra, A.K., Tombre, K. (eds.) GREC 1997. LNCS, vol. 1389, pp. 1–8. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  4. 4.
    Yu, Y., Samal, A., Seth, S.C.: A system for recognizing a large class of engineering drawings. IEEE Trans. on Pattern Analysis and Machine Intelligence 19(8), 868–890 (1997)CrossRefGoogle Scholar
  5. 5.
    Song, J., Su, F., Tai, C.-L., Cai, S.: An object-oriented progressive-simplification-based vectorization system for engineering drawings: model, algorithm, and performance. IEEE Trans. on Pattern Analysis and Machine Intelligence 24(8), 1048–1060 (2002)CrossRefGoogle Scholar
  6. 6.
    Song, J., Su, F., Cheng, J., Cai, S.: A knowledge-aided line network oriented vectorization method for engineering drawings. Pattern Analysis and Application 3(2), 142–152 (2000)CrossRefGoogle Scholar
  7. 7.
    Dori, D.: A syntactic/geometric approach to recognition of dimensions in engineering machine drawings. Computer Vision, Graphics and Image Processing 47, 271–291 (1989)CrossRefGoogle Scholar
  8. 8.
    Lai, C.P., Kasturi, R.: Detection of dimension sets in engineering drawings. IEEE Trans. on Pattern Analysis and Machine Intelligence 16(8), 848–855 (1994)CrossRefGoogle Scholar
  9. 9.
    Lin, S.C., Ting, C.K.: A new approach for detection of dimensions set in mechanical drawings. Pattern Recognition Letters 18(4), 367–373 (1997)CrossRefGoogle Scholar
  10. 10.
    Su, F., Song, J., Tai, C.-L., Cai, S.: Dimension recognition and geometry reconstruction in vectorization of engineering drawings. In: IEEE Proc. of Conf. on Computer Vision and Pattern Recognition, Hawaii, vol. 1, pp. 710–716 (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Feng Su
    • 1
  • Jiqiang Song
    • 1
  • Shijie Cai
    • 1
  1. 1.State Key Laboratory for Novel Software TechnologyNanjing UniversityNanjingChina

Personalised recommendations