Advertisement

Text/Graphics Separation in Maps

  • Ruini Cao
  • Chew Lim Tan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2390)

Abstract

The separation of overlapping text and graphics is a challenging problem in document image analysis. This paper proposes a specific method of detecting and extracting characters that are touching graphics. It is based on the observation that the constituent strokes of characters are usually short segments in comparison with those of graphics. It combines line continuation with the feature line width to decompose and reconstruct segments underlying the region of intersection. Experimental results showed that the proposed method improved the percentage of correctly detected text as well as the accuracy of character recognition significantly.

Keywords

Machine Intelligence Text Image Graphical Line Character Recognition Text Detection 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    G. Nagy, Twenty years of document image analysis in PAMI, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No. 1, pp. 38–62, January 2000CrossRefMathSciNetGoogle Scholar
  2. 2.
    D. S. Doermann, An introduction to vectorization and segmentation, in Graphics Recognition: Algorithms and Systems, K. Tombre and A. K. Chhabra (eds.), Lecture Notes in Computer Science 1389, Springer, pp. 1–8, 1998Google Scholar
  3. 4.
    C. L. Tan and P. O. Ng, Text extraction using pyramid, Pattern Recognition, Vol. 31, No. 1, pp. 63–72, 1998Google Scholar
  4. 5.
    D. Wang and S. N. Srihari, Analysis of form images, in Document Image Analysis, Bunke, P. S. P. Wang, H. Baird (eds.), World Scientific, pp. 1031–1051, 1994Google Scholar
  5. 6.
    S. Naoi, Y. Hotta, M. Yabuki, and A. Asakawa, Global interpolation in the segmentation of handwritten characters overlapping a border, Proceeding of 1st IEEE International Conference on Image Processing, pp. 149–153, 1994Google Scholar
  6. 7.
    J. Yoo, M. Kim, S. Y. Han, and Y. Kwon, Line removal and restoration of handwritten characters on the form documents, Proceeding of 4th International Conference on Document Analysis and Recognition, pp. 128–131, 1997Google Scholar
  7. 8.
    K. Lee, H. Byun, and Y. Lee, Robust reconstruction of damaged character images on the form documents. In Graphics Recognition: Algorithms and Systems, K. Tombre and A. K. Chhabra (eds.), Lecture Notes in Computer Science 1389, Springer, pp. 149–162, 1998Google Scholar
  8. 9.
    R. Kasturi, S. T. Bow, W. El-Masri, J. Shah, J. R. Gattiker, and U. B. Mokate, A system for interpretation of line drawings, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 12, No. 10, pp. 978–992, October 1990CrossRefGoogle Scholar
  9. 10.
    D. Dori and Liu W., Vector-based segmentation of text connected to graphics in engineering drawings, in Advances in Structural and Syntactical Pattern Recognition, P. Perner, P. Wang, A. Rosenfeld (eds.), Springer, pp. 322–331, 1996Google Scholar
  10. 11.
    Z. Lu, Detection of text regions from digital engineering drawings, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, No. 4, pp. 431–439, April 1998CrossRefGoogle Scholar
  11. 12.
    H. Luo, G. Agam, and I. Dinstein, Directional mathematical morphology approach for line thinning and extraction of character strings from maps and line drawings, Proceeding of 3rd International Conference on Document Analysis and Recognition, pp. 257–260, 1995Google Scholar
  12. 13.
    L. Li, G. Nagy, A. Samal, S. Seth, Y. Xu, Cooperative text and line-art extraction from a topographic map, Proceedings of 5th International Conference on Document Analysis and Recognition, pp. 467–470, 1999Google Scholar
  13. 14.
    D. Dori, Liu W. and M. Peleg, How to win a dashed line detection contest, in Graphics Recognition: methods and Applications, R. Kasturi and K. Tombre (eds.), Lecture Notes in Computer Science 1072, Springer, pp. 286–300, 1996Google Scholar
  14. 15.
    R. Jain, R. Kasturi, and B. G. Schunck, Machine Vision, MIT Press and McGraw-Hill, 1995Google Scholar
  15. 16.
    B. K. Jang and R. T. Chin, One-pass parallel thinning: analysis, properties, and quantitative evaluation, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 14, No. 11, pp. 1129–1140, November 1992CrossRefGoogle Scholar
  16. 17.
    T. Pavlidis, Algorithms for graphics and image processing, Computer Science Press, 1982Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Ruini Cao
    • 1
  • Chew Lim Tan
    • 1
  1. 1.School of ComputingNational University of SingaporeSingapore

Personalised recommendations