Advertisement

Sadhana

, Volume 27, Issue 6, pp 685–698 | Cite as

A knowledge-based approach for recognition of handwritten Pitman shorthand language strokes

  • P. Nagabhushan
  • Basavaraj S. Anami
Article

Abstract

The Pitman shorthand language (PSL) is a recording medium practised in all organizations, where English is the transaction medium. It has the practical advantage of high speed of recording, more than 120–200 words per minute, because of which it is universally acknowledged. This recording medium has its continued existence in spite of considerable developments in speech processing systems, which are not universally established yet. In order to exploit the vast transcribing potential of PSL a new area of research on automation of PSL processing is conceived. It has three major steps, namely, shape recognition of PSL strokes, their validation and English text production from these strokes.

The paper describes a knowledge-based approach for the recognition of PSL strokes. Information about location and the direction of the starting point and final point of strokes are considered the knowledge base for recognition of strokes. The work comprises preprocessing, determination of starting and final points, acquisition of quadrant knowledge, graph-based traversal and finally a rule-based inference process for generating phonetic equivalent of English language characters for the strokes. The proposed work is thoroughly tested for a large number of handwritten strokes.

Keywords

Pitman shorthand language character recognition English text production primitives knowledge base 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Gose E, Johnsonbaugh R, Jost S 1999Pattern recognition and image processing (New Delhi: Prentice Hall of India)Google Scholar
  2. Harowitz E, Sahani S 1976Fundamentals of data structures (Woodland Hills, CA: Computer Science Press)Google Scholar
  3. Hemanth Kumar G 1998Automation of text production from Pitman shorthand notes. Ph D thesis, University of Mysore, MysoreGoogle Scholar
  4. Kuroda K, Harada K, Hagiwara M 1999 Large scale online handwritten Chinese character recognition using successor method based on stochastic regular grammar.Pattern Recogn. 32: 1307–1315CrossRefGoogle Scholar
  5. Leedham C G, Downtown A C 1984 On-line recognition of short forms in Pitmans’ handwritten shorthand.Proc. 7th Int. Conf. on Pattern Recognition, Montreal, pp 2.1058–2.1060Google Scholar
  6. Leedham C G, Downtown A C 1986 On-line recognition of Pitmans’ handwritten shorthand — An evaluation potential.Int. J. Man-Machine Studies 24: 375–393CrossRefGoogle Scholar
  7. Leedham C G, Downtown A C 1987 Automatic recognition and transcription of Pitman’s handwritten shorthand — An approach to short forms.Pattern Recogn. 20: 341–348CrossRefGoogle Scholar
  8. Leedham C G, Downtown A C 1990 Automatic recognition and transcription of Pitman’s handwritten shorthand.Computer processing of handwriting (eds) R Plamondon, C G Leedham (Singapore: World Scientific)Google Scholar
  9. Leedham C G, Downtown A C, Brooks C P, Newell A F 1984 On-line acquisition of Pitman’s hand-written shorthand as a means of rapid data entry.Proc. Int. Conf. on Human-Computer Interaction, London, pp 2.86–2.91Google Scholar
  10. Nagabhushan P, Anami B S 1999 A knowledge based approach for composing English text from phonetic text documented through Pitman shorthand language.Int. Conf. On Computer Science (ICCS-99), New Delhi, pp 318–327Google Scholar
  11. Nagabhushan P, Anami B S 2000 A knowledge based approach for recognition of grammalogues and punctuation symbols useful in automatic English text generation from Pitman shorthand language documents.Proc. Natl. Conf. on Recent Trends in Advanced Computing (NCRTAC-2000), Thirunelveli, pp 175–183Google Scholar
  12. Nagabhushan P, Murli 2000 Tangent feature values and cornarity index to recognise handwritten PSL words.Proc. Natl. Conf. on Document Analysis and Recognition (NCDAR), Mandya, India, pp 49–56Google Scholar
  13. Patterson D W 1999Introduction to artificial intelligence and expert systems (New Delhi: Prentice Hall of India)Google Scholar
  14. Pitman I 1976Pitman shorthand instructor and key (Wheeler Publisher)Google Scholar
  15. Samouelian et al 1994 Knowledge based approach to English consonant recognition.Proc. Int. Conf. On Acoust. Speech & Signal Process., pp 77–80, Piscataway, NJGoogle Scholar

Copyright information

© Indian Academy of Sciences 2002

Authors and Affiliations

  • P. Nagabhushan
    • 1
  • Basavaraj S. Anami
    • 1
  1. 1.Department of Studies in Computer ScienceUniversity of Mysore, ManasgangotriMysoreIndia

Personalised recommendations