CFP last date
20 May 2024
Reseach Article

A Survey on Various OCR Errors

by Atul Kumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 143 - Number 4
Year of Publication: 2016
Authors: Atul Kumar
10.5120/ijca2016910142

Atul Kumar . A Survey on Various OCR Errors. International Journal of Computer Applications. 143, 4 ( Jun 2016), 8-10. DOI=10.5120/ijca2016910142

@article{ 10.5120/ijca2016910142,
author = { Atul Kumar },
title = { A Survey on Various OCR Errors },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2016 },
volume = { 143 },
number = { 4 },
month = { Jun },
year = { 2016 },
issn = { 0975-8887 },
pages = { 8-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume143/number4/25064-2016910142/ },
doi = { 10.5120/ijca2016910142 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:45:26.970028+05:30
%A Atul Kumar
%T A Survey on Various OCR Errors
%J International Journal of Computer Applications
%@ 0975-8887
%V 143
%N 4
%P 8-10
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Research has been carried out in correcting words in OCR text and mainly surrounds around (1) non word errors (2) isolated word error correction and context dependent word correction. Various kinds of techniques have been developed. This papers surveys various techniques in correcting these errors and determines which techniques are better.

References
  1. Bassil, Y., Alwani, M. 2012 . OCR post-processing error correction algorithm using Google's online spelling suggestion. J. Emer. Trends in Computing and Information Sciences. . Res. 3 (Jan. 2012).
  2. Niklas, K. 2010 Unsupervised post-correction of OCR errors. Master’s thesis,. Leibniz Universit¨, Hannover.
  3. Lehal, G. S., Singh, C. and Lehal, R. 2001. Shape Based Post Processor for Gurmukhi OCR. In Proceedings of the Sixth International Conference on Document Analysis and Recognition (ICDAR’01) IEEE Computer Society Press, USA.
  4. Kukich, K. 1992.Techniques for Automatically Correcting Words in Text. ACM Computing Surveys. Res. 24 (Dec. 1992), 377-439.
  5. Sharma, D. V., Lehal G. S. and Mehta S.2009. Shape Encoded Post Processing of Gurmukhi OCR. In proceedings of tenth International Conference on Document Analysis and Recognition.
  6. Yuan, L. X., Chew, L T, Xiaoqing, D., Changsong. 2004.Contextual Post-processing based on the Confusion Matrix in Offline Handwritten Chinese Script Recognition. In proceedings of 17th International Conference on Pattern Recognition ICPR.
  7. Karthika, M., Jawahar, C. V.2010.A Post-Processing Scheme for Malayalam using Statistical Sub-character Language Models. In proceedings of Ninth IAPR International Workshop On Document Analysis Systems, Boston, MA.
  8. Kolak, O. and Resnik, P.2005.OCR Post-Processing for Low Density Languages. In proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing.
  9. Bansal, V. and Sinha, K. M. R.1999.Partitioning and searching dictionary for correction of optically read Devnagri character strings. In Proceedings International Conference on Document Analysis and Recognition.
  10. Chaudhuri, B. B., Pal, U. 1998.A Complete Printed Bangla OCR systems. Pattern Recognition.1998. Res. 24 (Mar. 1998), 531-549
  11. Kernighan, M. D., Church, W. K. and Gale, A. W.1990.A Spelling Correction Program Based on a Noisy Channel Model. In Proceedings of the 13th conference on Computational linguistics.
Index Terms

Computer Science
Information Sciences

Keywords

OCR Errors NLP. Probability