iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://unpaywall.org/10.1007/3-540-63931-4_209
Combinatorial coarse classification method for OLCCR | SpringerLink
Skip to main content
Springer Nature Link
Log in

Combinatorial coarse classification method for OLCCR

  • Poster Session II
  • Conference paper
  • First Online:
Computer Vision — ACCV'98 (ACCV 1998)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1352))

Included in the following conference series:

  • 2670 Accesses

Abstract

This paper presents a new coarse classification method based on combination of two independent approaches for on-line Chinese character recognition (OLCCR). Through introducing a feedback control provided by the fine classifier, we are able to reach a good trade-off betweenprecision and speed. In the paper, we make some theoretical analysis on the form of combination, and compare it with competing methods. Both theoretical analysis and experimental results show that our method has the characteristics of high correct rate, good recognition speed, being easy to control and adaptable to various needs for practical application through parameter adjustment.

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

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

Reference

  1. Y.S Wu, X.Q.Ding, Chinese character recognition—principle, method and implement, Advanced education publishing house, 1992 (In Chinese)

    Google Scholar 

  2. C.C.Tappert, “The state of the art in on-line handwriting recognition”, IEEE Trans. Patt. Anal. Machine. Intell., Vol. 12, No. 8, pp.787–808, 1990

    Google Scholar 

  3. F.Nouboud and R.Plamondon, “On-line recognition of handprinted characters: suvery and beta tests”, Pattern Recognition, Vol.23, No.9, pp. 1031–1044, 1990

    Google Scholar 

  4. Y.Xia,S.P.Ma,Z.H.Yang,J.P.Gong and Y.Yang, “Method and system for on-line recognizing constraint free Chinese character”, The fifth Conference on Oriental Language, pp.85–89 (in Chinese)

    Google Scholar 

  5. T-Z.Lin and K-C.Fan, “Coarse classification of on-line chinese characteers via structure feature-based method”, Pattern Recognition, Vol.27, No. 10, pp. 1365–1377, 1994

    Google Scholar 

  6. Y-T.Tsay and W-H.Tsai, “Attribute string matching by split-and-merge for on-line chinese character recongnition”, IEEE Trans. Patt.,Anal. Mach. Intell., Vol. 15, No.2, pp.180–185, 1993

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Image Processing Group, Department of Electronic Engineering, Tsinghua University, 100084, Beijing, China

    Jing Zheng, Xiaoqing Ding, Youshou Wu & Fanxia Guo

Authors
  1. Jing Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaoqing Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Youshou Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fanxia Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Roland Chin Ting-Chuen Pong

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zheng, J., Ding, X., Wu, Y., Guo, F. (1997). Combinatorial coarse classification method for OLCCR. In: Chin, R., Pong, TC. (eds) Computer Vision — ACCV'98. ACCV 1998. Lecture Notes in Computer Science, vol 1352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63931-4_209

Download citation

  • DOI: https://doi.org/10.1007/3-540-63931-4_209

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63931-2

  • Online ISBN: 978-3-540-69670-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation