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Morphological Operations and Projection Profiles based Segmentation of Handwritten Kannada Document

Mamatha H. R, Srikantamurthy K Published in Pattern Recognition

International Journal of Applied Information Systems
Year of Publication 2012
© 2010 by IJAIS Journal
10.5120/ijais12-450704
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  1. Mamatha H.r and Srikantamurthy K. Article: Morphological Operations and Projection Profiles based Segmentation of Handwritten Kannada Document. International Journal of Applied Information Systems 4(5):13-19, October 2012. BibTeX

    @article{key:article,
    	author = "Mamatha H.r and Srikantamurthy K",
    	title = "Article: Morphological Operations and Projection Profiles based Segmentation of Handwritten Kannada Document",
    	journal = "International Journal of Applied Information Systems",
    	year = 2012,
    	volume = 4,
    	number = 5,
    	pages = "13-19",
    	month = "October",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

Segmentation is an important task of any Optical Character Recognition (OCR) system. It separates the image text documents into lines, words and characters. The accuracy of OCR system mainly depends on the segmentation algorithm being used. Segmentation of handwritten text of some Indian languages like Kannada, Telugu, Assamese is difficult when compared with Latin based languages because of its structural complexity and increased character set. It contains vowels, consonants and compound characters. Some of the characters may overlap together. Despite several successful works in OCR all over the world, development of OCR tools in Indian languages is still an ongoing process. Character segmentation plays an important role in character recognition because incorrectly segmented characters are unlikely to be recognized correctly. In this paper, a segmentation scheme for segmenting handwritten Kannada scripts into lines, words and characters using morphological operations and projection profiles is proposed. The method was tested on totally unconstrained handwritten Kannada scripts, which pays more challenge and difficulty due to the complexity involved in the script. Usage of the morphology made extracting text lines efficient by an average extraction rate of 94. 5% . Because of the varying inter and intra word gaps an average segmentation rate of 82. 35% and 73. 08% for words and characters respectively is obtained.

Reference

  1. K. Srikanta Murthy, G. Hemantha Kumar, P. Shivakumar and P. R. Ranganath. 2004. Nearest Neighbour Clustering approach for line and character segmentation in epigraphical scripts. In the proceedings of International Conference on Cognitive Systems (ICCS-2004), New Delhi, December 14-15, 2004.
  2. K. S. Sesh Kumar, A. M. Namboodiri, and C. V. Jawahar. 2006. Learning Segmentation of Documents with Complex Scripts. In the proceedings of ICVGIP 2006, LNCS 4338, pp. 749–760, 2006
  3. Zaidi Razak, Khansa Zulkiflee , Mohd Yamani Idna Idris, Emran Mohd Tamil, Mohd Noorzaily ,Mohamed Noor, Rosli Salleh, Mohd Yaakob ,Zulkifli Mohd Yusof and Mashkuri Yaacob,"Off-line Handwriting Text Line Segmentation : A Review" ,IJCSNS International Journal of Computer Science and Network Security, vol. 8 No. 7, July 2008 pp 12-20
  4. M. Arivazhagan, H. Srinivasan, S. N. Srihari. 2007. A Statistical Approach to Handwritten Line Segmentation. In Proceedings of SPIE Document Recognition and Retrieval XIV , San Jose, CA, February 2007
  5. Y. Li, Y. Zheng, D. Doermann, and S. Jaeger. 2006. A new algorithm for detecting text line in handwritten documents. In International Workshop on Frontiers in Handwriting Recognition, 2006, pp. 35–40
  6. L. Likforman-Sulem and C. Faure. 1994. Extracting text lines in handwritten documents by perceptual grouping. Advances in handwriting and drawing : a multidisciplinary approach,C. Faure, P. Keuss, G. Lorette and A. Winter Eds, Europia,Paris, 1994, pp. 117-135
  7. L. Likforman-Sulem, A. Hanimyan and C. Faure. 1995. A Hough based algorithm for extracting text lines in handwritten documents. in the proceedings of Third International Conference on Document Analysis and Recognition, Vol. 2, August 1995, pp. 774-777.
  8. C. Weliwitage, A. L. Harvey and A. B. Jennings. 2005. Handwritten Document Offline Text Line Segmentation. In Proceedings of Digital Imaging Computing: Techniques and Applications, 2005, pp. 184-187
  9. D. Sarkar and R. Ghose. A bottom up approach of line segmentation from handwritten text.
  10. U. pal ,P. P. Roy and J. Liados. 2010. Morphology based handwritten line segmentation using foreground and backgroud information. In the proceeding of Intl conference on Frontiers in Handwriting Recognation,2010
  11. L. Kaur N. K. Garg and M. K. Jindal. 2010. A new method for line segmentation of handwritten Hindi text. In the proceeding of 7th Intl conference on Information technology, pages 392–397, 2010.
  12. M. kundu M. Nasipuri S. Basu, C. Chaudhuri and D. K. Basu. 2007. "Text line extraction from multi-skewed handwritten documents". Patten Recognition, 40:1825–1839, 2007.
  13. G. Louloudis , B. Gatos , I. Pratikakis and C. Halatsis , 2009. "Line And Word Segmentation of Handwritten Documents " ,Journal Pattern Recognition archive Volume 42 Issue 12, December, 2009, pp 3169-3183
  14. F. Luthy, T. Varga, H. Bunke. 2007. ''Using Hidden Markov Models as a Tool for Handwritten Text Line Segmentation'', Ninth International Conference on Document Analysis and Recognition, Curitiba, Brazil, 2007, pp. 8-12
  15. Vijaya Kumar Koppula , Atul Negi . 2010. Using Fringe Maps for Text Line Segmentation in Printed or Handwritten Document Images. In the proceedings of 2010 Second Vaagdevi International Conference on Information Technology for Real World Problems,2010,pp 83-88
  16. Naresh Kumar Garg, Lakhwinder Kaur and M. K. Jindal. 2010. A New Method for Line Segmentation of Handwritten Hindi Text. In the proceedings 2010 Seventh International Conference on Information Technology,2010, pp 392-397
  17. Rajiv Kumar and Amardeep Singh, 2010. Detection and Segmentation of Lines and Words in Gurmukhi Handwritten Text. In the proceedings of IEEE 2nd International Advance Computing Conference,2010,pp 353-356
  18. G. Louloudis , N. Stamatopoulos , B. Gatos . 2009. A Novel Two Stage Evaluation Methodology for Word Segmentation Techniques. In the proceedings of 10th International Conference on Document Analysis and Recognition,2009, pp 686-690
  19. Richard G. Casey and Eric Lecolinet. 1996. "A survey of Methods and Strategies in Character Segmentation", IEEE Transactions On Pattern Analysis And Machine Intelligence, vol. 18, no. 7, July 1996 pp 690-706
  20. Rafael C. Gonzalez ,Richard E. Woods and Steven L. Eddins ,Digital Image Processing using MATLAB, Indian Edition,2009,pp 348-361.
  21. Alireza Alaei, P. Nagabhushan and Umapada Pal. 2011. A Benchmark Kannada Handwritten Document Dataset and its Segmentation. In the proceedings of International Conference on Document Analysis and Recognition, 2011,pp 141-145.
  22. B. Gatos, N. Stamatopoulos and G. Louloudis. 2009. "ICDAR 2009 Handwriting Segmentation Contest," Proc. of 10th ICDAR, 2009, pp. 1393–1397.
  23. A. Alaei, U. Pal and P. Nagabhushan. 2011. "A new scheme for unconstrained handwritten text-line segmentation", Pattern Recognition, 44 (4), 2011, pp. 917–928.
  24. V. N. Manjunath Aradhya and C. Naveena. 2011. Text Line Segmentation of Unconstrained Handwritten Kannada Script. In the proceedings of ICCCS'11, 2011, pp 231-234.

Keywords

OCR, Morphological operations, Projection Profiles, Segmentation