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Arabic Cheque Processing System: Issues and Future Trends

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Digital Document Processing

Part of the book series: Advances in Pattern Recognition ((ACVPR))

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References

  1. Abouhaibah, I. (1998). Recognition of off-line cursive handwriting. Computer Vision and Image Understanding, 71(1), pp. 19–38.

    Article  Google Scholar 

  2. Al Ohali, Y. (2002). Handwritten Word Recognition: Application to Arabic Cheque Processing. Ph.D. Thesis, Concordia University, Montreal, Canada.

    Google Scholar 

  3. Al-Badr, B. and Mahmoud, S. (1995). Survey and bibliography of Arabic optical text recognition. Signal Processing, 41, pp. 49–77.

    Article  MATH  Google Scholar 

  4. Allen, J. (1995). Natural Language Understanding. Menlo Park, CA: The Benjamin/Cummings Publishing Company, Inc.

    MATH  Google Scholar 

  5. Alohali, Y., Cheriet, M., and Suen, C.Y. (2000). Databases for recognition of handwritten Arabic cheques. Proceedings of the Seventh IWFHR, Amster-dam, The Netherlands, pp. 601–606.

    Google Scholar 

  6. Alshebeili, S., Nabawi, A., and Mohmoud, S. (1997). Arabic character recog-nition using 1-D slices of the character spectrum. Signal Processing, 56, pp. 59–75.

    Article  MATH  Google Scholar 

  7. Al-Yousefi, H. and Upda, S. (1990). Recognition of handwritten Arabic char-acters via segmentation. Arab Gulf Journal for Scientific Research, 8, pp. 49–59.

    Google Scholar 

  8. Amin, A.(2000). Recognition of printed Arabic text based on global features and decision tree learning techniques. Pattern Recognition, 33, pp. 1309–1323.

    Article  Google Scholar 

  9. Ayat, N.E. (2003). Automatic model selection for support vectors machines: application to the recognition of handwritten digits. PhD thesis. Montreal, Canada: ETS, Université du Québec.

    Google Scholar 

  10. Blanz, V., Scholkopf, B., Bulthoff, H.H., Burges, C., Vapnik, V., and Vetter, T. (1996). Comparison of view-based object recognition algorithms using realistic 3d models. ICANN, pp. 251–256.

    Google Scholar 

  11. Cheriet, M. and Suen, C.Y. (1993). Extraction of key letters for cursive script recognition. Pattern Recognition Letters, 14, pp. 1009–1017.

    Article  Google Scholar 

  12. Chim, Y., Kassim, A., and Ibrahim, Y. (1998). Dual classifier system for hand printed alphanumeric character recognition. Pattern Analysis & Applications, 1, pp. 155–162.

    Article  MATH  Google Scholar 

  13. Chris, J.C.B. and Schölkopf, B. (1997). Improving the accuracy and speed of support vector machines. In: M.C. Mozer, M.I. Jordan, and T. Petsche (Eds.). Advances in Neural Information Processing Systems. CAmbridge, MA: The MIT Press, Volume 9, p. 375.

    Google Scholar 

  14. Cortes, C. and Vapnik, V. (1995). Support-vector networks. Machine Learning, 20(3), pp. 273–297.

    MATH  Google Scholar 

  15. Dehghan, M., Faez, K., Ahmadi, M., and Shridhar, M. (2001). Handwritten Farsi (Arabic) word recognition: a holistic approach using discrete HMM. Pattern Recognition, 34, pp. 1057–1065.

    Article  MATH  Google Scholar 

  16. Gilloux, M. and Leroux, M. (1993). Recognition of cursive script amounts on postal cheques. European Conference. Dedicated to Postal Technologies. Nantes, France, pp. 705–712.

    Google Scholar 

  17. Guillevic, D. (1995). Unconstrained handwriting recognition applied to the processing of bank cheques. PhD thesis. Montreal, Quebec, Canada: Concor-dia University.

    Google Scholar 

  18. Guillevic, D. and Suen, C.Y. (1998). Recognition of legal amounts on bank cheques. Pattern Analysis and Applications, 1, pp. 28–41.

    Article  Google Scholar 

  19. Heutte, L., Paquet, T., Moreau, J., Lecourtier, Y., and Olivier, C. (1998). A structural/statistical feature based vector for handwritten character recogni-tion. Pattern Recognition Letters, 19, pp. 629–641.

    Article  Google Scholar 

  20. Il-Seok, Oh. and Suen, C.Y. (1998). Distance features for neural network-based recognition of handwritten characters. IJDAR, pp. 73–88.

    Google Scholar 

  21. Kato, Y. and Yasuhara, M. (2000). Recovery of drawing order from single-stroke handwritten images. IEEE Transactions on PAMI, 22(9), pp. 938–949.

    Google Scholar 

  22. Kaufmann, G. and Bunke, H. (2000). Automatic reading of cheque amounts. Pattern Analysis & Applications, 3, pp. 132–141.

    Article  Google Scholar 

  23. Kim, G. and Goveindaraju, V. (1997). A lexicon driven approach to hand-written word recognition for real time applications. IEEE Transactions on PAMI, 19(4), pp. 366–379.

    Google Scholar 

  24. Li, Z., Tang, S., and Yan, S. (2002). Pattern recognition with support vec-tor machines. Lecture Notes in Computer Science, chapter Multi-Class SVM Classifier Based on Pairwise Coupling. Berlin, Heidelberg: Springer, Volume 2388, pp. 321–333.

    Google Scholar 

  25. Loncaric, S. (1998). A survey of shape analysis techniques. Pattern Recognition, 31(8), pp. 983–1001.

    Article  Google Scholar 

  26. Madhvanath, S. and Govindaraju, V. (1992). Using Holistic Features in Handwritten Word Recognition. United States Postal Service (USPS), Vol-ume 1, pp. 183–198.

    Google Scholar 

  27. Miled, H., Cheriet, M., and Olivier, C. (1998). Multi-level Arabic handwritten words recognition. Proceedings of Advances in Pattern Recognition, Sydney, Australia, pp. 944–951.

    Google Scholar 

  28. Miled, H., Olivier, C., Cheriet, M., and Lecourtier, Y. (1997). Coupling ob-servation/letter for a Markovian modelisation applied to the recognition of Arabic handwriting. ICDAR, pp. 580–583.

    Google Scholar 

  29. Moreira, M. and Mayoraz, E. (1998). Improved pairwise coupling classifica-tion with correcting classifiers. IDIAP-RR 09, IDIAP, 1997. Proceedings of the Tenth European Conference on Machine Learning.

    Google Scholar 

  30. Osuna, E., Freund, R., and Girosi, F. (1997). Training Support Vector Machines: An Application to Face Detection. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Puerto Rico, pp. 130–136.

    Google Scholar 

  31. Schmidt, M.S. (1996). Identifying speakers with support vector networks. Proceedings of the 28th Symposium on the Interface (INTERFACE-96). Sydney, Australia, July 1996.

    Google Scholar 

  32. Scholkopf, B. (1997). Support vector learning. PhD thesis. Berlin, Germany: Universität Berlin.

    Google Scholar 

  33. Strathy, N.W.(1993). Master thesis. Montreal, Canada: Concordia University.

    Google Scholar 

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Cheriet, M., Al-Ohali, Y., Ayat, N.E., Suen, C.Y. (2007). Arabic Cheque Processing System: Issues and Future Trends. In: Chaudhuri, B.B. (eds) Digital Document Processing. Advances in Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-84628-726-8_10

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  • DOI: https://doi.org/10.1007/978-1-84628-726-8_10

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84628-501-1

  • Online ISBN: 978-1-84628-726-8

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