Skip to main content
SpringerLink
Log in

Recognition of legal amounts on bank cheques

  • Published:
Pattern Analysis and Applications Aims and scope Submit manuscript

Abstract

This article describes the recognition of legal amounts of a bank cheque processing system developed at CENPARMI. The preprocessing, sentence to word segmentation and word recognition approaches are presented along with some critical reviews. The overall engine is a combination of a global feature scheme with an HMM module. The global features consist of the encoding of the relative position of the ascenders, descenders and loops within a word. The HMM uses one feature set based on the orientation of contour points as well as their distance to the baselines. Our system is fully trainable, reducing to a strict minimum the number of hand-set parameters. The system is also modular and independent of specific languages as we have to deal with at least two languages in Canada, namely English and French. The system can be easily adapted to read other European languages based on the Roman alphabet. The system is continuously tested on data from the local phone company, and we report here the results on a balanced French database of approximately 2000 cheques with specified amounts.

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. Guillevic D. Unconstrained handwriting recognition applied to the recognition of bank cheques. PhD thesis, Concordia University, Montréal, Canada, September 1995. (http://www.cenparmi.con-cordia.ca/-people/didier/thesis/)

  2. Guillevic D. and Suen CY. Cursive script recognition applied to the processing of bank cheques. Proceedings of the International Conference Document Analysis and Recognition, Montréal, Canada, August 1995; 11–15

  3. Gilloux M, Leroux M. Recognition of cursive script amounts on postal cheques. Proceedings of the European Conference of Postal Technologies, Nantes, France, June 1993; 705–712

  4. Kim G. Recognition of offline handwritten words and its extension to phrase recognition. PhD thesis, State University of New York at Buffalo, March 1996

  5. Moreau J-V. A new system for automatic reading of postal checks. Proceedings of the International Workshop on Frontiers of Handwriting Recognition, Bonas, France, 1991; 121–132

  6. Liu K, Suen CY, Nadal C. Automatic extraction of items from cheque images for payment recognition. Proceedings of the International Conference Pattern Recognition, Vienna, Austria, 1996, 798–802

  7. Strathy NW, Suen CY. A new system for reading handwritten zip codes. Proceedings of the International Conference Document Analysis and Recognition, Montréal, Canada, August 1995; 74–77

  8. Strathy NW. A method for segmentation of touching handwritten numerals. Master's thesis, Concordia University, Montréal, Québec, Canada, September 1993

  9. Strathy NW, Suen CY, Krzyzak A. Segmentation of handwritten digits using contour features. Proceedings of the International Conference Document Analysis and Recognition. Tsukuba, Japan, October 1993; 577–580

  10. Guillevic D, Suen CY. Cursive script recognition: A sentence level recognition scheme. Proceedings of the International Workshop on Frontiers of Handwriting Recognition, Taipei, Taiwan, December, 1994

  11. Seni G, Cohen E. External word segmentation of off-line handwritten text lines. Pattern Recognition 1994; 27(1): 41–52

    Google Scholar 

  12. Paquet T, Lecourtier Y. Handwriting recognition: application on bank cheques. Proceedings of the International Conference Document Analysis and Recognition, Saint Malo, France, September 1991; 749–757

  13. Lyon RF, Yaeger LS. On-line hand-printing recognition with neural networks. Proceedings of the International Conference Microelectronics for Neural Networks and Fuzzy Systems, Lausanne, Switzerland, February 1996

  14. Guillevic D, Suen CY. HMM word recognition engine. Proceedings of the International Conference Document Analysis and Recognition, Ulm, Germany, August 1997; 544–547

  15. Seni G. Large Vocabulary Recognition of On-line Handwritten Cursive Words. PhD thesis, State University of New York at Buffalo, August 1995

  16. Bengio Y, Le Cun Y, Henderson D. Globally trained handwritten word recognizer using spatial representation, convolutional neural networks and hidden Markov models. In Advances in Neural Information Proceesing Systems, volume 6, San Mateo, CA, 1994; 937–944

  17. Favata JT. Recognition of Cursive, Discrete and Mixed Handwritten Words Using Character, Lexical and Spatial Contraints. PhD thesis, State University of New York at Buffalo, 1993

  18. Lang KJ, Waibel AH, Hinton GE. A time-delay neural network architecture for isolated word recognition. Neural Networks 1990; 3: 23–43

    Google Scholar 

  19. Rabiner LR. A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE 1989: 257–286

  20. Caesar T, Gloger JM, Mandler E 1989: Design of a system for off-line recognition of handwritten word images. Proceedings of the European Conference Postal Technologies, pages 156–161, Nantes, France, June 1993; 156–161

  21. Caesar T, Gloger JM, Mandler E. Preprocessing and feature extraction for a handwriting recognition system. Proceedings of the International Conference Document Analysis and Recognition, Tsukuba Science City, Japan, October 1993; 408–411

  22. Deller JR, Proakis JG, Hansen, JHL. Discrete-Time Processing of Speech Signals. Prentice Hall, 1993

  23. Suen CY, Nadal C, Legault R, Mai TA, Lam L. Computer recognition of unconstrained handwritten numerals. Proceedings of the IEEE 1992; 80(7): 1162–1180

    Google Scholar 

  24. Ho TK, Hull JJ, Srihari SN. Decision combination in multiple classifier systems. IEEE Trans PAMI 1994; 16(1): 66–75

    Google Scholar 

  25. Smith SJ, Bourgoin MO, Sims K, Voorhees HL. Handwritten character classification using nearest neighbor in large databases. IEEE Trans PAMI 1994; 16(9): 915–919

    Google Scholar 

  26. Goldberg DE. Genetics Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, 1989

  27. Ho TK. A Theory of Multiple Classifier Systems and Its Application to Visual Word Recognition. PhD thesis, State University of New York at Buffalo, May 1992

  28. Hull JJ. A database for handwritten text recognition research. IEEE Trans PAMI 1994; 16(5): 550–554

    Google Scholar 

  29. Leroux M, Lethelier E, Gilloux M, Lemarie B. Automatic reading of handwritten amounts on French cheques. International Journal of Pattern Recognition Artificial Intelligence 1997 (To appear-Special issue on bank check recognition)

Download references

Author information

Author notes

  1. D. Guillevic

    Present address: Pattern Analysis Technology Group, C&C Media Research Laboratories, NEC Corporation, 1-1, Miyazaki 4-Chome, Miyamae-Ku, 216, Kawasaki, Japan

Authors and Affiliations

  1. CENPARMI, Concordia University, Montréal, Québec, Canada

    D. Guillevic & C. Y. Suen

Authors
  1. D. Guillevic
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. C. Y. Suen
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Guillevic, D., Suen, C.Y. Recognition of legal amounts on bank cheques. Pattern Analysis & Applic 1, 28–41 (1998). https://doi.org/10.1007/BF01238024

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01238024

Keywords

Search

Navigation