Open Access   Article Go Back

Extraction of Tamil Characters from a Handwritten Document using Connected Component Labeling

D. Rajalakshmi1 , S.K. Jayanthi2

  1. Dept. of Computer Science, Vellalar College for Women (Bharathiar University), Coimbatore, India.
  2. Dept. of Computer Science, Vellalar College for Women (Bharathiar University), Coimbatore, India.

Correspondence should be addressed to: rajalakshmi.d@gmail.com.

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-9 , Page no. 141-146, Sep-2017

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v5i9.141146

Online published on Sep 30, 2017

Copyright © D. Rajalakshmi, S.K. Jayanthi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: D. Rajalakshmi, S.K. Jayanthi, “Extraction of Tamil Characters from a Handwritten Document using Connected Component Labeling,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.9, pp.141-146, 2017.

MLA Style Citation: D. Rajalakshmi, S.K. Jayanthi "Extraction of Tamil Characters from a Handwritten Document using Connected Component Labeling." International Journal of Computer Sciences and Engineering 5.9 (2017): 141-146.

APA Style Citation: D. Rajalakshmi, S.K. Jayanthi, (2017). Extraction of Tamil Characters from a Handwritten Document using Connected Component Labeling. International Journal of Computer Sciences and Engineering, 5(9), 141-146.

BibTex Style Citation:
@article{Rajalakshmi_2017,
author = {D. Rajalakshmi, S.K. Jayanthi},
title = {Extraction of Tamil Characters from a Handwritten Document using Connected Component Labeling},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2017},
volume = {5},
Issue = {9},
month = {9},
year = {2017},
issn = {2347-2693},
pages = {141-146},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1445},
doi = {https://doi.org/10.26438/ijcse/v5i9.141146}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v5i9.141146}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1445
TI - Extraction of Tamil Characters from a Handwritten Document using Connected Component Labeling
T2 - International Journal of Computer Sciences and Engineering
AU - D. Rajalakshmi, S.K. Jayanthi
PY - 2017
DA - 2017/09/30
PB - IJCSE, Indore, INDIA
SP - 141-146
IS - 9
VL - 5
SN - 2347-2693
ER -

VIEWS PDF XML
948 427 downloads 329 downloads
  
  
           

Abstract

Writer identification is a challenging task for the reason that it requires textural features and structural features. Textural features like grey-level co-occurrence matrices, Gabor filters can be extracted from entire page or a block of text. The structural features like slant and skew, character height, stroke width, frequency of loops or blobs etc. also characterize the handwriting style. Before extracting character level features it is a prerequisite to segment the document image into characters. This paper proposes a connected component oriented approach to segment an image of handwritten Tamil document into individual characters. The features extracted from these characters then can be used for writer identification.

Key-Words / Index Term

Writer Identification, Handwritten documents, Segmentation, Connected Component, Tamil Script

References

[1] Srihari, Sargur N., Sung-Hyuk Cha, Hina Arora, and Sangjik Lee. "Individuality of handwriting." Journal of Forensic Science, Vol.47, No. 4,pp.1-17,2002.
[2] Hertel, Caroline, and Horst Bunke. "A set of novel features for writer identification." International Conference on Audio-and Video-Based Biometric Person Authentication. Springer, Berlin, pp. 679-687, 2003.
[3] Bulacu, Marius, and Lambert Schomaker. "Combining multiple features for text-independent writer identification and verification." In Proc. of Tenth International Workshop on Frontiers in Handwriting Recognition, La Baule, pp. 281–286, 2006.
[4] H. Fujisawa, Y.Nakano and K.Kurino, “Segmentation methods for character recognition from segmentation to document structure analysis”, Proceedings of the IEEE, Vol.80, No.7, pp. 1079-1092, 1992.
[5] Richard G. Casey and Eric Lecolinet, “A Survey of Methods and Strategies in Character Segmentation”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.18, No. 7, pp. 690-706, 1996.
[6] Bansal V, Sinha R M K., “Segmentation of Touching and Fused Devanagari Characters.” Pattern Recognition.,Vol.35, No.4, pp. 875-893,2002.
[7] Munish Kumar, M. K. Jindal, and R. K. Sharma. "Segmentation of isolated and touching characters in offline handwritten Gurmukhi script recognition." International Journal of Information Technology and Computer Science (IJITCS),Vol.6,No.2,p.58, 2014.
[8] Saba, Tanzila, Ghazali Sulong, and Amjad Rehman. "A survey on methods and strategies on touched characters segmentation." International Journal of Research and Reviews in Computer Science,Vol. 1,No.2, pp. 103-114, 2010.
[9] Ye Xiangyun, Mohamed Cheriet, and Ching Y. Suen. "Stroke-model-based character extraction from gray-level document images." IEEE Transactions on Image Processing, Vol.10,No.8, pp.1152-1161,2001.
[10] Sridevi, N., and P. Subashini, "Segmentation of Text Lines and Characters in Ancient Tamil Script Documents using Computational Intelligence Techniques." International Journal of Computer Applications,Vol. 52, No.14,pp.7-12, 2012.
[11] Vassilis Papavassiliou, Themos Stafylakis, Vassilis Katsouros, and George Carayannis, “Handwritten document image segmentation into text lines and words”. Pattern Recognition, vol. 43, pp. 369 – 377, 2010.
[12] Dharmapryia C. Bandara,Vasile Palade, and Ruskan Batuwita, “A Customizable Fuzzy System for Offline Handwritten Character Recognition,” International Journal on Artificial Intelligence Tools, vol. 20, no. 3, pp. 425–455, 2011.
[13]Mamatha, H. R., and K. Srikantamurthy. "Morphological Operations and Projection Profiles based Segmentation of Handwritten Kannada Document." International Journal of Applied Information Systems (IJAIS), Vol. 4, No.5, pp.13-19,2012.
[14] Siddhartha Banerjee,Bibek Ranjan Ghosh,Arka Kundu ,"Handwritten Character Recognition from Bank Cheque",International Journal of Computer Sciences and Engineering ,Vol.4,No.1, pp.99-104,2016.
[15] He, L., Ren, X., Gao, Q., Zhao, X., Yao, B. and Chao, Y. "The connected-component labeling problem: A review of state-of-the-art algorithms". Pattern Recognition,Vol. 70,pp. 25-43, 2017.
[16] N. Otsu, “A threshold selection method from grey level histogram”. IEEE transactions on Systems, Man, and Cybernetics, Vol. 9, pp. 62-66, 1979.
[17] Rafael C.Gonzalez , Richard E.Woods, “Digital Image Processing”,Third Edition, Dorling Kindersley India Pvt. Ltd., India, pp. 645-647,2009.
[18] Gurpreet Kaur and Jaskaranjit Kaur, "A Comparative Study of Image Demosaicing", International Journal of Computer Sciences and Engineering, Vol.3, Issue.7, pp.98-102, 2015.
[19] D.Rajalakshmi,S.K.Jayanthi,"Collection of Offline Tamil Handwriting Samples and Database Creation", International Journal of Advanced Research in Computer and Communication Engineering,Vol. 5, Issue 8, pp. 196-199, 2016.