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Reseach Article

Yoruba Handwriting Word Recognition Quality Evaluation of Preprocessing Attributes using Information Theory Approach

by Jumoke F. Ajao, Stephen O.olabiyisi, Elijah O.omidiora, Odetunji O. Odejobi
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 9 - Number 1
Year of Publication: 2015
Authors: Jumoke F. Ajao, Stephen O.olabiyisi, Elijah O.omidiora, Odetunji O. Odejobi
10.5120/ijais15-451357

Jumoke F. Ajao, Stephen O.olabiyisi, Elijah O.omidiora, Odetunji O. Odejobi . Yoruba Handwriting Word Recognition Quality Evaluation of Preprocessing Attributes using Information Theory Approach. International Journal of Applied Information Systems. 9, 1 ( June 2015), 18-23. DOI=10.5120/ijais15-451357

@article{ 10.5120/ijais15-451357,
author = { Jumoke F. Ajao, Stephen O.olabiyisi, Elijah O.omidiora, Odetunji O. Odejobi },
title = { Yoruba Handwriting Word Recognition Quality Evaluation of Preprocessing Attributes using Information Theory Approach },
journal = { International Journal of Applied Information Systems },
issue_date = { June 2015 },
volume = { 9 },
number = { 1 },
month = { June },
year = { 2015 },
issn = { 2249-0868 },
pages = { 18-23 },
numpages = {9},
url = { https://www.ijais.org/archives/volume9/number1/749-1357/ },
doi = { 10.5120/ijais15-451357 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T18:59:39.368254+05:30
%A Jumoke F. Ajao
%A Stephen O.olabiyisi
%A Elijah O.omidiora
%A Odetunji O. Odejobi
%T Yoruba Handwriting Word Recognition Quality Evaluation of Preprocessing Attributes using Information Theory Approach
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 9
%N 1
%P 18-23
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents an approach to evaluate the quality of handwritten words using the set of features in the preprocessing stages. This is to determine the effect of various stages of preprocessing of the recognition of Yoruba handwritten characters. We demonstrate our methods using handwritten words samples of the domain of Yoruba medical terminology collected from indigenous Yoruba literate writers. Samples were digitized at 300dpi to facilitate much detail representation of the image dataset. We study the impact of entropy measure for an intuitive interpretation of the analysis of the handwritten words. From the experiment carried out, it was observed that the entropy measure of handwritten word is higher than the typewritten word. This implies that the Information content of the handwritten word is affected by perturbations which need to be removed using appropriate image preprocessing tools to obtain low entropy measure which implies same information content as the original.

References
  1. Mori, S. , Suen, C. and Yamamoto, K. , 1992 "Historical Review of OCR Research and Development". Proceedings of IEEE, Vol. 80 No. 7, pp. 1029–1058.
  2. Saritha, B. S. and Hemanth S. , 2009 "An Efficient Hidden Markov Model for Offline Handwritten Numeral Recognition," InterJRI Computer Science and Networking, Vol. 1, pp. 7-12.
  3. Marinai, S. , Gori, M. and Soda, G. 2005 "Artificial Neural Networks for Document Analysis and Recognition," Pattern Analysis and Machine Intelligence, IEEE Transactions, Vol. 27, No. 1, pp. 23 – 35.
  4. Jain, A. K. , Duin, R. P. , and Jianchang M. "Statistical pattern recognition: a review," Pattern Analysis and Machine Intelligence, IEEE Transactions, Vol. 22, No. 1, pp. 4 – 37, January 2000.
  5. Duda, R. O. Hart, P. E and Stork, D. G. 2001 "Pattern classification," 2nd Edition, Wiley.
  6. Bishop, C. M. 2006 "Pattern Recognition and Machine Learning," Springer.
  7. Theodoridis S. and Koutroumbas, K. 2009 "Pattern Recognition", 4th Edition, Academic Press, San Diego,.
  8. Bunke, H. 2003 "Recognition of Cursive Roman handwriting – Past, Present and Future,"Document Analysis and Recognition Seventh International Conference, Edinburgh, pp. 448–459.
  9. Cheriet, M. , Kharma, N. Liu, C-L. and Suen, C. "Character Recognition Systems: A Guide for Students and Practitioners," John Wiley, New York, November 2007.
  10. Plamondon R. and Srihari, S. N. 2000 "On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey, "IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No. 1.
  11. Arica N. and Yarman-Vural, F. T. , 2001 "An Overview of Character Recognition Focused on Off-Line Handwriting," Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions, Vol. 31, No. 2.
  12. Bamgbose, A. 1976 "Yoruba Orthography," Ibadan University Press, pp. 15-27.
  13. Omnigot 2013 "The Yoruba alphabets and it pronunciation,". Accessed at http://www. omniglot. com/writing/yoruba. htm.
  14. Lee, H. and Verma, B. 2012 "Binary Segmentation Algorithm for English Cursive Handwriting Recognition," Pattern Recognition,Elsevier, Vol. 45, No. 4, pp. 1306–1317.
  15. El-Yacoubi, A. Gilloux, M. , Sabourin R. and Suen, C. Y. 1999 "An HMM-Based Approach for Off-Line Unconstrained Handwritten Word Modeling and Recognition," Pattern Analysis and Machine Intelligence, IEEE Transactions, Vol. 21, No. 8, pp. 752 – 760.
  16. Gunter, S. and Bunke, H. 2003 "Ensembles of Classifiers for Handwritten Word Recognition," Document Analysis and Recognition, Vol. 5, No. 4, pp. 224-232.
  17. Oliveira, L. S. , Sabourin, R. , Bortolozzi, F. and Suen, C. Y. 2002 "Automatic Recognition of Handwritten Numerical Strings: A Recognition and Verification Strategy," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, No. 11.
  18. Impedovo D. and Pirlo, G. 2014 "Zoning Methods for Handwritten Character Recognition: A Survey," Pattern Recognition, Handwriting Recognition and other PR Applications, Vol. 47, No. 3, pp. 969–981, Elsevier.
  19. Desai, A. A. 2010 "Gujarati Handwritten Numeral Optical Character Reorganization through Neural Network," Pattern Recognition, Vol. 43, No. 7, pp. 2582–2589, Elsevier.
  20. Kessentini, Y. , Paquet T. and Hamadou, A. B. 2010 "Off-Line Handwritten Word Recognition Using Multi-Stream Hidden Markov Models" Pattern Recognition Letters, Vol. 31, No. 1, pp. 60 – 70.
  21. Femwa, O. D. 2012 "Development of a Writer-Independent Online, Handwritten Character Recognition System Using Modified Hybrid Neural Network Model," PhD. Thesis, Ladoke Akintola University of Technology, Ogbomoso,.
  22. Ibraheem, O. and Odejobi, O. A. 2011 "A System for the Recognition of Handwritten Yoru?ba? Characters," AGIS 2011 Ethiopia, ObafemiAwolowo University, Ile-Ife, Nigeria,. Retrieved from http://www. slideshare. net/aflat/a-system-for-the-recognition-of-handwritten-yoruba-characters.
  23. Niblack, W. 1986 "An Introduction Letters to Digital Image Processing," Prentice Hall, Englewood Cliffs.
  24. Abu-Mostafa, Y. S. and Psaltis, D. 1985 "Image Normalization by Complete Moments," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 7, No. 1.
  25. Kwag, H. K. , Kim, S. S. H. Jeony, S. H and G. S. Lee, 2002 "Efficient Skew Estimation and Correction Algorithm for Document Images", Image and vision Computing, Vol. 20, pp. 25-35.
  26. B. Yu, B. and Jain, A. K. 1996 "A Robust and Fast Skew Detection Algorithm for Generic Documents", Pattern Recognition, Vol. 29, Issue 10, pp. 1599-1629, October.
  27. Shannon, C. E. , 1948 "A Mathematical Theory of Communication. " The Bell System Technical Journal, Vol. 27, pp. 623–656.
Index Terms

Computer Science
Information Sciences

Keywords

Yoruba Entropy Handwritten word and Optical Character Reader.