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Reseach Article

Offline Recognition of Handwritten Urdu Characters using B Spline Curves: A Survey

by Mohd Jameel, Sanjay Kumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 157 - Number 1
Year of Publication: 2017
Authors: Mohd Jameel, Sanjay Kumar
10.5120/ijca2017912604

Mohd Jameel, Sanjay Kumar . Offline Recognition of Handwritten Urdu Characters using B Spline Curves: A Survey. International Journal of Computer Applications. 157, 1 ( Jan 2017), 28-34. DOI=10.5120/ijca2017912604

@article{ 10.5120/ijca2017912604,
author = { Mohd Jameel, Sanjay Kumar },
title = { Offline Recognition of Handwritten Urdu Characters using B Spline Curves: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2017 },
volume = { 157 },
number = { 1 },
month = { Jan },
year = { 2017 },
issn = { 0975-8887 },
pages = { 28-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume157/number1/26797-2016912604/ },
doi = { 10.5120/ijca2017912604 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:02:47.214299+05:30
%A Mohd Jameel
%A Sanjay Kumar
%T Offline Recognition of Handwritten Urdu Characters using B Spline Curves: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 157
%N 1
%P 28-34
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Handwritten Character Recognition is an active area of research in the field of pattern recognition and image processing for last two decades as there is an urgent need of having a successful Script Recognition System to convert handwritten documents into computer understandable form which is applicable for various purposes. Several research studies have been carried out for recognition of other scripts like Chinese, Japanese, English, Devanagari, etc. but the research regarding Urdu Script is still immature due to cursive and variable nature of Urdu characters. The requirement of offline Urdu HCR systems is increasing because of the expansion of technology and the convenience for users. In this paper, a detailed survey of Urdu HCR techniques with respect to feature extraction developed so far alongwith their efficiency and accuracy has been presented. The paper also presents a new proposed B-Spline Curve approximation approach for feature extraction of offline isolated Urdu handwritten characters.

References
  1. Shahzad N, Paulson B and Hammond Tracy “Urdu Qaeda: Recognition System for Isolated Urdu Characters” Sketch Recognition Lab. Texas A&M University,2009.
  2. H. Aljuaid and D. Muhamad, "Offline Arabic Character Recognition using Genetic Approach: A Survey".
  3. R. I. Zaghloul, E. F. Alrawashdeh, D. Mohammad, and K. Bader, “Multilevel Classifier in Recognition of Handwritten Arabic Characters" Journal of Computer Science 7 (4): 512-518, ISSN 1549-3636, 2011.
  4. H. Aljuaid, Z. Muhammad and M. Sarfraz, "A Tool to Develop Arabic Handwriting Recognition System Using Genetic Approach", Journal of Computer Science 6 (6): 597- 602ISSN 1549-3636, 2010.
  5. Saeeda Naz, Arif Iqbal, Umar “An OCR System For Printed Nasta’liq Script: A Segmentation Based Approach” ISBN: 978-1-4799-5754-5/14/©2014 IEEE.
  6. S.T.Javed, S.Hussain “Improving Nastalique-specific pre-recognition process for Urdu OCR” Proceedings of the 13th International Multi-topic IEEE Conference (INMIC'09),2009,pp.1–6.
  7. S.M.Azam,Z.A.Mansoor,M.Sharif, “On fast recognition of isolated characters by constructing character signature database” Proceedings of the International Conference on Emerging Technologies (ICET'06),2006,pp.568–575.
  8. S.T. Javed “Investigation into a segmentation based OCR for the Nastaleeq writing system (Master's thesis)”. National University of Computer & Emerging Sciences, Lahore, Pakistan, 2007.
  9. H. Malik, M.A. Fahiem, “Segmentation of printed Urdu scripts using structural features” Proceedings of the 2nd International Conference inVisualisation (VIZ'09), 2009,pp.191–195.
  10. A.Abidi, I.Siddiqi, K.Khurshid “Towards searchable digital Urdu libraries-a word spotting based retrieval approach” Proceedings of the International Conference on Document Analysis and Recognition (ICDAR'11),2011, pp. 1344–1348.
  11. D.B. Megherbi,S.M.Lodhi,A.J.Boulenouar “Fuzzy-logic-model-based technique with application to Urdu character recognition” Proceedings of the SPIE Applications of Artificial NN in Image Processing V3962 (2000) 13–24.
  12. Z.A.Shah “Ligature based optical character recognition of Urdu-Nastaleeq font” Proceedings of the 6th International Multi-topic IEEE Conference (INMIC'02), 2002,pp.25–25
  13. Z.Ahmad, J.K.Orakzai, I.Shamsher, A.Adnan “Urdu Nastaleeq optical character recognition” Proceedings of the World Academy of Science, Engineering and Technology, vol.26,2007.
  14. S.A.Sattar,S.Haque,M.K.Pathan,Q.Gee “Implementation challenges for nastaliq character recognition” Wireless Networks, Information Processing and Systems, Communications in Computer and Information Science, vol.20.Springer,Berlin,Heidelberg,2009,pp.279–285.
  15. S.A.Sattar,S.ulHaq,M.K.Pathan “A finite state model for Urdu nastalique optical character recognition” International Journal of Computer Science and Network Security(IJCSNS)9(9)(2009).
  16. S.A. Hussain, S.Zaman, M.Ayub “A self organizing map based Urdu Nasakh character recognition” Proceedings of the International Conference on Emerging Technologies (ICET'09), Islamabad, Pakistan,2009,pp.267–273.
  17. J. Tariq, U.Nauman, M.U.Naru “Soft converter: a novel approach to construct OCR for printed urdu isolated characters” Proceedings of the 2nd International Conference on Computer Engineering and Technology (ICCET’10), vol.3,Singapore, 2010,pp.V3–495–V3–498.
  18. S.A.Husain “A multi-tier holistic approach for Urdu Nastaliq recognition” Proceedings of the 6th International Multi-topic IEEE Conference (INMIC'02), 2002,pp.528–532.
  19. U.Pal, A.Sarkar “Recognition of printed Urdu script” Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR2003),2003,pp.1183–1187.
  20. S.M. Lodhi, M.A.Matin “Urdu character recognition using Fourier descriptors for optical networks” Proceedings of the Photonic Devices and Algorithms for ComputingVII,vol.SPIE5907,2005.
  21. S.T. Javed, S. Hussain, A. Maqbool, S. Asloob, S. Jamil, H. Moin “Segmentation Free Nastalique Urdu OCR” World Academy of Science, Engineering and Technology
  22. S.Zaman, W.Slany, F.Sahito “Recognition of segmented Arabic/Urdu characters using pixel values as their features” Proceedings of the 1st International Conference on Computer and Information Technology (ICCIT'2012),2012.
  23. N. B. Amor and N. E. Ben Amara," Combining a hybrid Approach for Features Selection and Hidden Markov Models in Multi-font Arabic Characters Recognition", IEEE Second International Conference on Document Image Analysis for Libraries (DIAL’06) 0-7695-2531-8/06, 2006.
  24. N. Ben Amor, M. Zarai, and N. E. Ben Amara ", Neuro-Fuzzy approach in the recognition of Arabic Characters " 0-7803-9521-2/06/$20.00 §2006 IEEE.
  25. R. I. Zaghloul, E. F. Alrawashdeh, D. Mohammad, and K. Bader “Multilevel Classifier in Recognition of Handwritten Arabic Characters" Journal of Computer Science 7 (4): 512-518, ISSN 1549-3636, 2011.
  26. G. A. Abandah, K. S. Younis and M. Z. Khedher, "Handwritten Arabic Character Recognition Using Multiple Classifiers Based on Letter Form" Proc. 5th IASTED Int'l Conf. on Signal Processing, Pattern Recognition, & Applications (SPPRA, Innsbruck, Austria, 2008.
  27. O. Hachour "The Combination of Fuzzy Logic and Expert System for Arabic Character Recognition" 3rd International IEEE Conference Intelligent Systems, September 2006.
  28. M. N., K. Faez "Recognition of Multi-font Farsi / Arabic Characters Using a Fuzzy Neural Network" IEEE.
  29. M. W. Sagheer, C. L. He, N. Nobile, and C. Y. Suen “A New Large Urdu Database for Off-Line Handwriting Recognition” in Proceedings of International Conference on Image Analysis and Processing (ICIAP’09), 2009.
  30. S. Basu, N. Das, R. Sarkar, M. Kundu, M. Nasipuri, and D. K. Basu “A Novel Framework for Automatic Sorting of Postal Documents with Multi-Script Address Blocks” Pattern Recognition., vol. 43, no. 10, pp. 3507–3521, 2010.
  31. M. I. Razzak, S. A. Hussain, A. Belaïd, M. Sher, and others, “Multi-font Numerals Recognition for Urdu Script based Languages” Int. J. Recent Trends Eng., 2009.
  32. Z. Shokoohi, A. M. Hormat, F. Mahmoudi, and H. Badalabadi “Persian handwritten numeral recognition using Complex Neural Network and non-linear feature extraction” First Iranian Conference on Pattern Recognition and Image
  33. A. Nooraliei “Persian handwritten digits recognition by using zoning and histogram projection” AI & Robotics and 5th Robo Cup Iran Open International Symposium (RIOS) 3rd Joint Conference of, 2013, pp. 1–5.
  34. A. Roy, N. Das, R. Sarkar, S. Basu, M. Kundu, and M. Nasipuri “An axiomatic fuzzy set theory based feature selection methodology for handwritten numeral recognition” Proceedings of the 48th Annual Convention of Computer Society of India-Vol I, 2014, pp. 133–140.
  35. Xiabi Liu and Yunde Jia “ Character Stroke Extraction Based on B-spline Curve Matching by Constrained Alternating Optimization” Ninth International Conference on Document Analysis and Recognition (ICDAR 2007)
  36. K. T. Miura, R. Sato and S. Mori “A Method of Extracting Curvature Features and its Application to Handwritten Character Recognition” 0-8186-7898-4/97 /1997 IEEE.
  37. Zhongkang “Extraction and Optimization of B-Spline PBD Templates for Recognition of Connected Handwritten Digit Strings ” IEEE Transactions On Pattern Analysis and Machine Intelligence, Vol. 24, No. 1, January 2002.
  38. H. Tirandaz, A. Nasrabadi and J. Haddadnia “Curve Matching and Character Recognition by Using B-Spline Curves” IACSIT International Journal of Engineering and Technology Vol.3, No.2, April 2011
  39. I.K. Pathan, A.A.Ali “Recognition of offline handwritten isolated Urdu character” Advances in Computational Research 4(1)(2012)117–121.
  40. A.Ali, M. Ahmad, N.Rafiq, J.Akber, U.Ahmad, Akmal “Language independent optical character recognition for handwritten text” Proceedings of the 8th International Multi-topic IEEE Conference (INMIC'04),2004,pp.79–84.
  41. O. Mukhtar, S.Setlur, V.Govindaraju “Experiments on Urdu text recognition” Guide to OCR for Indic Scripts, Advances in Pattern Recognition. Springer, London, 2010, pp.163–171
  42. M.W.Sagheer, C.L.He, N.Nobile, C.Y.Suen “A new large Urdu database for off-Line handwriting recognition “
  43. M. Yusuf, T.Haider “Recognition of handwritten Urdu digits using shape context” Proceedings of the 8th International Multi-topic IEEE Conference (INMIC'04), 2004,pp.569–572.
  44. M.W.Sagheer, C.L.He,N.Nobile,C.Y.Suen “Holistic Urdu handwritten word recognition using support vector machine” Proceedings of the 20th International Conference on Pattern Recognition (ICPR’10),2010,pp.1900–1903.
  45. S. Basu, N.Das, R.Sarkar, M.Kundu, M.Nasipuri, D.K.Basu “A novel framework for automatic sorting of postal documents with multi-script address blocks” Pattern Recognition43(10)(2010)3507–3521.
  46. M.I. Razzak, F.Anwar, S.A.Husain, A.Belaïd, M.Sher “HMM and fuzzy logic: a hybrid approach for online Urdu script-based languages' character recognition” Knowledge Based Systems 23(8)(2010)914–923.
  47. S.A. Husain, A.Sajjad, F.Anwar “Online Urdu character recognition system” Proceedings of the IAPR Conference on Machine Vision Applications (MVA'07), 2007,pp.98–101.
  48. Saeeda Naz1, Saad B. “Arabic Script based Digit Recognition Systems” International Conference on Recent Advances in Computer Systems (RACS 2015)
  49. S. Naz, et al. “The optical character recognition of Urdu-like cursive scripts” Pattern Recognition (2013), http: //dx.doi.org/10.1016/j.patcog.2013.09.037i
  50. Khoi Nguyen-Tan and Nguyen Nguyen-Hoang “Handwriting Recognition Using B-Spline Curve” ICCASA 2012, LNICST 109, pp. 335–346, 2013.
Index Terms

Computer Science
Information Sciences

Keywords

Handwritten Urdu Character Recognition B-Spline curve Offline