Frontiers in Handwriting Recognition

  • Conference paper
Fundamentals in Handwriting Recognition

Part of the book series: NATO ASI Series ((NATO ASI F,volume 124))

Abstract

The evolution of computer front panels and punch tapes and punch cards to teletype interfaces and the keyboards of modern personal computers shows that the problem of a faster man-machine interaction has been a great scientific and technological challenge since the origin of computers. During the last decades many efforts have been made in the technological field to design special peripheral devices such as the graphic tablet, the scanner, the mouse, electronic ink and so on. Furthermore, efforts have also been made to study models of writing generation motor and recognition algorithms. But in spite of technological and architectural progress made in the field of computers, the problem of a friendly interaction between man and computer at least at the same friendly level that exists with a sheet of paper and a pencil, still remains unresolved.

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

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
EUR 29.95
Price includes VAT (Germany)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
EUR 85.59
Price includes VAT (Germany)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
EUR 106.99
Price includes VAT (Germany)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. S. Impedovo, L. Ottaviano, S. Occhinegro, Optical Character Recognition — A Survey, International Journal of Pattern Recognition and Artificial Intelligence 5(1,2), 1–24 (1991).

    Article  Google Scholar 

  2. R.G. Casey, H. Takahashi, Experience in segmenting and classifying the NIST data base, in [35].

    Google Scholar 

  3. V. Govindaraju, S.N. Srihari, Separating handwritten text from interfering stroke, in [35].

    Google Scholar 

  4. H. Nishida, T. Suzuki, S. Mori, Thin line representation from contour representation of handprinted characters, in [35].

    Google Scholar 

  5. P. Morasso, A. Pareto, S. Pagliano, Neural models for handwriting recognition, in [35].

    Google Scholar 

  6. L.R.B. Schomaker, H.-L. Teulings, Stroke-versus character-based recognition of on-line, connected cursive script, in [35].

    Google Scholar 

  7. H.-L Teulings, L.R.B. Schomaker, Unsupervised learning of prototype allographs in cursive script recognition, in [35].

    Google Scholar 

  8. Y.-J. Liu, J.-W. Tai, An on-line Chinese character recognition system for handwritten in Chinese calligraphy, in [35].

    Google Scholar 

  9. J.-W. Tai, Y.-J. Liu, L.-Q. Zhang, A new approach for feature extraction and feature selection of handwritten Chinese character recognition, in [35].

    Google Scholar 

  10. S.L. Shiau, S J. Kung, A.J. Hsieh, J.W. Chen, M.C.Kao, Stroke-order free on-line Chinese character recognition by structural decomposition method, in [35].

    Google Scholar 

  11. R. Fenrich, Segmentation of automatically located handwritten numeric strings, in [35].

    Google Scholar 

  12. M.J.J. Holt, M.M. Beglou, S. Datta, Slant-independent letter segmentation for off-line cursive script recognition, in [35].

    Google Scholar 

  13. J.J. Hull, T.K. Ho, J. Favata, V. Govindaraju, S.N. Srihari, Combination of segmentation-based and wholistic handwritten word recognition algorithms, in [35].

    Google Scholar 

  14. T. Fujisaki, H.S.M. Beigi, C.C. Tappert, M. Ukelson, C.G. Wolf, Online recognition of unconstrained handprinting: a stroke based system and its evaluation, in [35].

    Google Scholar 

  15. C.A. Higgins, D.M. Ford, A new segmentation method for cursive script recognition, in [35].

    Google Scholar 

  16. K. Sakai, H. Asami, Y. Tanabe, Advanced Application Systems for handwritten Character Recognition, in [35].

    Google Scholar 

  17. K. Yamamoto, H. Yamada, T. Saito, Current state of recognition method for Japanese characters and database for research of handprinted character recognition, in [35].

    Google Scholar 

  18. A.C. Downton, R.W.S. Tregidgo, C.G. Leedham, Hendrawan, Recognition of handwritten British postal addresses, in [35].

    Google Scholar 

  19. P.S.P. Wang, M.V. Nagendraprasad, A.Gupta, A neural net based ‘hybrid’ approach to handwritten numeral recognition, in [35].

    Google Scholar 

  20. F. Chiavetta, V. Di Gesù, G. Dimauro, G. Gerardi, S. Impedovo, G. Pirlo, D. Tegolo, A Transputer-based system for multi-stroke character recognition, in [35].

    Google Scholar 

  21. J.V. Moreau, A new system for automatic reading of postal checks, in [35].

    Google Scholar 

  22. Y. Nakano, Advanced application — systems for handwritten character recognition, in [35].

    Google Scholar 

  23. K. Seino, Y. Tanabe, K. Sakai, A linguistic post processing based on word occurrence probability, in [35].

    Google Scholar 

  24. G. Dimauro, S. Impedovo, G. Pirlo, Uncertainty in the recognition process: some considerations on human variable behaviour, in [35].

    Google Scholar 

  25. C.Y. Suen, J. Guo, Z.C. Li, Computer and human recognition of handprinted characters by parts, in [35].

    Google Scholar 

  26. J.C. Simon, O.Baret, Cursive words recognition, in [35].

    Google Scholar 

  27. J. Camillerapp, G. Lorette, G. Menier, H. Oulhadj, J.C. Pettier, Off-line and on-line methods for cursive handwriting recognition, in [35].

    Google Scholar 

  28. A. Zahour, B. Taconet, A. Faure, Machine recognition of arabic cursive writing, in [35].

    Google Scholar 

  29. B. Taconet, A. Zahour, A. Faure, A new global off-line recognition method for handwritten words, in [35].

    Google Scholar 

  30. I.J. Evett, C.J. Wells, F.G. Keenan, T. Rose, R J. Whitrow, Using linguistic information to aid handwriting recognition, in “From Pixels to Features III”, S.Impedovo and J.C.Simon eds., Elsevier 1992.

    Google Scholar 

  31. I. Yoshimura, M. Yoshimura, On line signature verification incorporating the direction of pen movement — An experimental examination of the effectiveness, in [35].

    Google Scholar 

  32. R. Plamondon, P. Yergeau, J.J. Brault, A multi-level signature verification system, in [35].

    Google Scholar 

  33. G. Dimauro, S. Impedovo, G. Pirlo, A stroke-oriented approach to signature verification, in [35].

    Google Scholar 

  34. P. Brittan, M.C. Fairhurst, An approach to handwritten signature verification using a high performance parallel architecture, in [35].

    Google Scholar 

  35. S. Impedovo, J.C. Simon (eds.): From Pixels to Features III — Frontiers in Handwriting Recognition Elsevier 1992.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1994 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Impedovo, S. (1994). Frontiers in Handwriting Recognition. In: Impedovo, S. (eds) Fundamentals in Handwriting Recognition. NATO ASI Series, vol 124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-78646-4_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-78646-4_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-78648-8

  • Online ISBN: 978-3-642-78646-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Navigation