Skip to main content
SpringerLink
Log in

Segmentation of stick text based on sub connected area analysis

  • Published:
Journal of Computer Science and Technology Aims and scope Submit manuscript

Abstract

A new stick text segmentation method based on the sub connected area analysis is introduced in this paper. The foundation of this method is the sub connected area representation of text image that can represent all connected areas in an image efficiently. This method consists mainly of four steps: sub connected area classification, finding initial boundary following point, finding optimal segmentation point by boundary tracing, and text segmentation. This method is similar to boundary analysis method but is more efficient than boundary analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Kahan S, Pavlidis T, Baird H S. On the recognition of printed characters of any font and size.PAMI, 1987, 9(2): 274–288.

    Google Scholar 

  2. Kimura F, Shridhar M. Segmentation-recognition algorithm for zip code field recognition.MVA, 1992, 5: 199–210.

    Article  Google Scholar 

  3. Liang S, Shridhar M, Ahmadi M. Segmentation of touching characters in printed document recognition.PR, 1994 27(6): 825–840.

    Google Scholar 

  4. Tsujimoto S, Asada H. Major components of a complete text reading system.Proc. IEEE, 1992, 80(7): 1133–1149.

    Article  Google Scholar 

  5. Bayer T A, Krebel U H G. Cut Classification for segmentation. InICDAR93, 1993, pp. 565–568.

  6. Wang J, Jean J. Segmentation of merged characters by neural networks and shortest path.PR, 1994, 27(5): 649–658.

    Google Scholar 

  7. Fujisawa H, Nakano Y, Kurino K. Segmentation methods for character recognition: From segmentation to document structure analysis.Proc. IEEE, 1992, 80(7): 1079–1092.

    Article  Google Scholar 

  8. Westall J M, Narasimha M S. Vertex directed segmentation of handwritten numerals.PR, 26(10): 1473–1486.

  9. Strathy N W, Suen C Y, Krzyzak A. Segmentation of handwritten digits using contour features. InICDAR93, 1993, pp. 577–580.

  10. Gao Jingbo, Tang Long, Liu Wenyin and Tang Zesheng. Segmentation and recognition of dimension texts in engineering drawings. InProc. the 3rd International Conference on Document Analysis and Recognition, Montreal, CANADA, 1995, pp. 528–531.

  11. Pavlidis T. Structural Pattern Recognition. Springer-Verlag, New York, 1977.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. CAD Center, Department of Computer Science and Technology, Tsinghua University, 100084, Beijing, P.R. China

    Gao Jingbo, Li Xinyou & Tang Zesheng

Authors
  1. Gao Jingbo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Li Xinyou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tang Zesheng
    View author publications

    You can also search for this author in PubMed Google Scholar

Additional information

Supported by the National "863" Hi-Tech Program of China.

Gao Jingbo is a Ph.D. candidate in the Department of Computer Science and Technology, Tsinghua University. He received his B.E. degree from Tsinghua in 1993. His research area is engineering drawing recognition.

Li Xinyou is an Associate Professor in the Department of Computer Science and Technology, Tsinghua University. He received his Ph.D. degree from Tsinghua University in 1991. His research areas are engineering drawing recognition, computer graphics.

Tang Zesheng is a Professor in the Department of Computer Science and Technology, Tsinghua University. His research areas are engineering drawing recognition, computer graphics.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gao, J., Li, X. & Tang, Z. Segmentation of stick text based on sub connected area analysis. J. of Comput. Sci. & Technol. 13, 55–62 (1998). https://doi.org/10.1007/BF02946614

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02946614

Keywords

Search

Navigation