CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Degraded Script Identification for Indian Language- A Survey

by Manoj Kumar Shukla, Haider Banka
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 108 - Number 6
Year of Publication: 2014
Authors: Manoj Kumar Shukla, Haider Banka
10.5120/18914-0222

Manoj Kumar Shukla, Haider Banka . Degraded Script Identification for Indian Language- A Survey. International Journal of Computer Applications. 108, 6 ( December 2014), 11-22. DOI=10.5120/18914-0222

@article{ 10.5120/18914-0222,
author = { Manoj Kumar Shukla, Haider Banka },
title = { Degraded Script Identification for Indian Language- A Survey },
journal = { International Journal of Computer Applications },
issue_date = { December 2014 },
volume = { 108 },
number = { 6 },
month = { December },
year = { 2014 },
issn = { 0975-8887 },
pages = { 11-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume108/number6/18914-0222/ },
doi = { 10.5120/18914-0222 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:42:15.510778+05:30
%A Manoj Kumar Shukla
%A Haider Banka
%T Degraded Script Identification for Indian Language- A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 108
%N 6
%P 11-22
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The working module of any Optical character Recognition system almost depends upon printing and paper of the input document image. A number of OCR techniques are available and claim correctly identified accuracy in printed document image in Indian and foreign script. A few report have been found on the recognition of the degraded Indian language document. The degradation in any scanned printed document can be of many types. In this paper, we focus a survey of degraded script identification for Indian Language document.

References
  1. S. N. Srihari and S. W. Lam, "Character recognition", Center of Excellence for Document Analysis and Recognition (CEDAR), Technical Report, 1995.
  2. M. E. Stevens, "Automatic character recognition-State-of-the-art report", National Bureau of Standards & Technology, Tech. Note 112, Washington, USA, 1961.
  3. S. Mori, C. Y. Suen and K. Yamamoto, "Historical review of OCR research and development", Proceedings of the IEEE, Vol. 80(7), pp. 1029-1058, 1992.
  4. U. Pal and B. B. Chaudhuri, "Indian script character recognition: a survey", Pattern Recognition, Vol. 37(9), pp. 1887-1899, 2004.
  5. S. Mori, K. Yamamoto and M. Yasuda, "Research on machine recognition of handprinted characters", IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. 6(4), pp. 386–405, 1984.
  6. G. Nagy, "At the frontiers of OCR", Proceedings of the IEEE, Vol. 80(7), pp. 1093-1100, 1992.
  7. R. Plamondon and S. N. Srihari, "On-line and off-line handwritten recognition: a comprehensive survey", IEEE Transactions on PAMI, Vol. 22(1), pp. 63–84, 2000.
  8. C. Y. Suen, R. Legault, C. Nadal, M. Cheriet and L. Lam, "Building a new generation of handwriting recognition systems", Pattern Recognition Letters, Vol. 14(4), pp. 305-315, 1993.
  9. U. Pal and B. B. Chaudhuri, "Computer recognition of printed Bangla script",International Journal of Systems Science, Vol. 26, pp. 2107-2123, 1995.
  10. U. Pal and B. B. Chaudhuri, "Printed Devanagari script OCR system", Vivek, Vol. 10(1), pp. 12-24, 1997.
  11. G. S. Lehal and C. Singh, "A complete machine printed Gurmukhi OCR system", Vivek, Vol. 16(3), pp. 10-17, 2006.
  12. M. Bosker, "Omnidocument technologies", Proceedings of the IEEE, Vol. 80(7), pp. 1066-1078, July 1992.
  13. T. Pavlidis, "Problems in recognising poorly printed text", in Symposium on Document Analysis and Information Retrieval(SDAIR), pp. 163-172, 1992.
  14. S. V. Rice, F. R. Jenkins and T. A. Nartker, "The fourth annual test of OCR accuracy", Technical Report 95-04, ISRI, University of Nevada, Las Vegas, pp. 11-50, 1995.
  15. J. Rocha and T. Pavlidis, "A solution to the problem of touching and broken characters", in the Proceedings of the 2nd International Conference on Document Analysis and Recognition (ICDAR), pp. 602-605, 1993.
  16. C. Fang, Deciphering Algorithms for Degraded Document Recognition, Ph. D. thesis, State University of New York at Buffalo, 1997.
  17. H. Bunke and P. S. P. Wang, Handbook of Character Recognition and Document Image Analysis, World Scientific Publishing Company, 1997.
  18. Stephen V. Rice, George Nagy and Thomas A. Nartker, Optical Character Recognition: An Illustrated Guide to the Frontier, Kluwer Academic Publications, 1999.
  19. S. Mori, H. Nishida and H. Yamada, Optical Character Recognition, John Wiley & Sons, 1999.
  20. J. Mantas, "An overview of character recognition methodologies", Pattern Recognition, Vol. 19(6), pp. 425-430, 1986.
  21. V. K. Govindan and A. P. Shivaprasad, "Character recognition-A review", Pattern Recognition, Vol. 23 (7), pp. 671-683, 1990.
  22. C. Y. Suen, M. Berthod and S. Mori, "Automatic recognition of hand printed characters- the state of the art", Proceedings of the IEEE, Vol. 68(4), pp. 469-487, 1980.
  23. S. Impedovo, L. Ottaviano and S. Occhinegro, "Optical character recognition- a survey", International Journal Pattern Recognition and Artificial Intelligence, Vol. 5(1-2), pp. 1-24, 1991.
  24. Q. Tian. P. Zhang. T. Alexander and Y. Kim, "Survey: omnifont-printed character recognition", in the proceedings of Visual Communications and Image Processing SPIE, Vol. 1606, pp. 260-268, 1991.
  25. A. K. Jain, R. P. W. Duin and J. Mao, "Statistical pattern recognition: a review", IEEE Transactions on PAMI, Vol. 22(1), pp. 4-37, 2000.
  26. R. Kasturi and L. O'Gorman, "Document image analysis: a bibliography", Machine Vision and Applications, Vol. 5(3), pp. 231-243, 1992.
  27. C. C Tappert, C. Y. Suen and T. Wakahara, "The state of the art in on-line handwriting recognition", IEEE Transactions on PAMI, Vol. 12(8), pp. 787-808,1990.
  28. T. Wakahara, H. Murase and K. Odaka, "On-line handwriting recognition",Proceedings of the IEEE, Vol. 80(7), pp. 1181-1194, 1992.
  29. F. Nouboud and R. Plamondon, "On-line recognition handprinted characters: survey and beta tests", Pattern Recognition, Vol. 23(9), pp. 1031-1044, 1990.
  30. S. D. Connell, R. M. K. Sinha and A. K. Jain, "Recognition of unconstrained on-line Devanagari characters", in the Proceedings of 15th International Conference on Pattern Recognition (ICPR), Vol. 2, Spain, pp. 368-371, 2000. 31] S. D. Connell and A. K. Jain, "Template-based online character recognition", Pattern Recognition, Vol. 34(1), pp. 1-14, 2001.
  31. F. Bortolozzi, A. Britto Jr. , L. S. Oliveria and M. Morita, "Recent advances in handwriting recognition", in the Proceedings of International Workshop on Document Analysis (IWDA), India, pp. 1-30, 2005.
  32. S. W. Lee, "Off-line recognition of totally unconstrained handwritten numerals Using multiplayer cluster neural network", IEEE Transactions on PAMI, Vol. 18(6), pp. 648-652, 1996.
  33. F. El-Khaly and M. A. Sid-Ahmed, "Machine recognition of optically captured machine printed Arabic text", Pattern Recognition, Vol. 23(11), pp. 1207-1214, 1990.
  34. A. Amin, "Off-line Arabic character recognition- a survey", in the Proceedings of 4th ICDAR, pp. 596-599, 1997.
  35. L. M. Lorigo and V. Govindaraju, "Offline Arabic handwriting recognition: a survey", IEEE Transactions on PAMI, Vol. 28(5), pp. 712-724, 2006.
  36. T. H. Hildebrandt and W. Liu, "Optical recognition of handwritten Chinese characters: Advances since 1980", Pattern Recognition, Vol. 26(2), pp. 205-225,1993.
  37. C. L. Liu, S. Jaeger and Masaki Nakagawa, "Online recognition of Chinese characters: the state-of-the-art", IEEE Transactions on PAMI, Vol. 26(2), pp. 198- 213, 2004.
  38. R. G. Casey and E. Lecolinet, "A survey of methods and strategies in character segmentation", IEEE Transactions on PAMI, Vol. 18(7), pp. 690-706, 1996.
  39. C. E. Dunn and P. S. P. Wang, "Character segmentation techniques for handwritten text - a survey", in the Proceedings of 11th ICPR, Vol. 2, pp. 577-580, 1992.
  40. Y. Lu, "Machine printed character segmentation - an overview", Pattern Recognition,Vol. 28(1), pp. 67-80, 1995.
  41. Y. Lu and M. Shridhar, "Character segmentation in handwritten words – an overview", Pattern Recognition, Vol. 29(1), pp. 77-96, 1996.
  42. R. L. Hoffman and J. W. McCullough, "Segmentation methods for recognition of machine-printed characters", IBM Journal of Research and Development, Vol. 15(2),pp. 153-165, 1971.
  43. H. S. Baird, S. Kahan and T. Pavlidis, "Components of an omnifont page reader", in the Proceedings of 8th ICPR, Paris, pp. 344-348, 1986.
  44. S. Tsujimoto and H. Asada, 1992, "Major components of a complete text reading system", Proceedings of the IEEE, Vol. 80(7), pp. 1133-1149, 1992.
  45. S. Liang, M. Shridhar and M. Ahmadi, "Segmentation of touching characters in printed document recognition", Pattern Recognition, Vol. 27(6), pp. 825-840, 1994.
  46. J. Wang and J. S. N. Jean, "Segmentation of merged characters by neural networks and shortest path", Pattern Recognition, Vol. 27(5), pp. 649-658, 1994.
  47. R. G. Casey and G. Nagy, "Recursive segmentation and classification of composite character patterns", in the Proceedings of 6th ICPR, pp. 1023-1026, 1982.
  48. S. W. Lee, D. J. Lee and H. S. Park, "A new methodology for gray-scale character segmentation and recognition", IEEE Transactions on PAMI, Vol. 18(10), pp. 1045- 1050, 1996.
  49. S. Tsujimoto and H. Asada, "Resolving ambiguity in segmenting touching characters", in the Proceedings of 1st ICDAR, pp. 701-709, 1991.
Index Terms

Computer Science
Information Sciences

Keywords

OCR Degraded Script.

Powered by PhDFocusTM