research-article

Touching character segmentation of Devanagari script

Authors:

Mahesh JangidAuthors Info & Claims

ICCCNT '16: Proceedings of the 7th International Conference on Computing Communication and Networking Technologies

Article No.: 26, Pages 1 - 5

https://doi.org/10.1145/2967878.2967908

Published: 06 July 2016 Publication History

Abstract

Segmentation of characters is one of the major step in OCR system. Devanagari script is a two dimensional form of symbol. It is very inconvenient to treat each form of character as a separate symbol because such combinations are very large in number. Segmentation is a process which separates words into characters. In this paper, we deal with segmentation of offline handwritten document especially touching character segmentation also we have discussed the process involved in touching character segmentation and the problem in those processes with their solution. The proposed method is tested on the database set of 250 handwritten touching characters. Experimental results indicate that the method used correctly segments the touching characters.

References

[1]

Jangid, Mahesh. "Devanagari isolated character recognition by using statistical features." International Journal of Computer Science and Engg 3.2 (2011): 2400--2407.

[2]

Bag, Soumen, and Ankit Krishna. "A Structural Approach for Segmentation of Unconstrained Handwritten Hindi Words." 2014 Fourth International Conference of Emerging Applications of Information Technology (EAIT). IEEE,

Digital Library

[3]

Ankur Kumar Aggarwal, Aman Kumar Aggarwal. "Devanagari Script Conjunct Characters Segmentation Based on Character Structural Properties by Horizontal Projection" ISSN: 0976-8491 (Online) | ISSN: 2229--4333 (Print) IJCST Vol. 4, Issue 2, April-June 2013

[4]

Bansal, Veena, and R. M. K. Sinha. "Segmentation of touching and fused Devanagari characters." Pattern recognition 35.4 (2002): 875--893.

[5]

Mr. Dipak V. Koshti, Mrs. Sharvari Govilkar. "Segmentation of Touching Characters in Handwritten Devanagari Script." UACEE International Journal of Computer Science and its Applications - Volume 2: Issue 2 {ISSN 2250 - 3765}

[6]

Xu, Liang, et al. "An over-segmentation method for single-touching Chinese handwriting with learning-based filtering." International Journal on Document Analysis and Recognition (IJDAR) 17.1 (2014): 91--104.

Digital Library

[7]

Liu, Ke, Yea S. Huang, and Ching Y. Suen "Identification of fork points on the skeletons of handwritten Chinese characters." Pattern Analysis and Machine Intelligence, IEEE Transactions on 21.10 (1999): 1095--1100.

Digital Library

[8]

B.Hari Kumar, N. Sateesh. "Segmentation of Touching Characters in Indian Scripts" International Journal of Science and Research (IJSR) ISSN (Online): 2319--7064 Index Copernicus Value (2013): 6.14 | Impact Factor (2013): 4.438

[9]

Kapoor, Shuchi, and Vivek Verma. "Fragmentation of handwritten touching character in Devanagri Script". International Journal of Information Technology, Modeling and Computing (IJITMC) Vol 2: 11--21.

[10]

Alok Kumar, Madhuri Yadav, Tushar Patnaik, Bhupendra Kumar. "A Survey on Touching Character Segmentation" International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249--8958, Volume-2, Issue-3, February 2013

[11]

Jayadevan, R., et al. "Offline recognition of Devanagari script: A survey." Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on 41.6 (2011): 782--796.

Digital Library

[12]

Sarkar, Ram, Bibhash Sen, Nibaran Das, and Subhadip Basu. "Handwritten Devanagari Script Segmentation: A nonlinear Fuzzy Approach." arXiv preprint arXiv:1501.05472 (2015).

[13]

Saraf, Vedgupt, and D. S. Rao. "Devnagari script character recognition using genetic algorithm for get better efficiency." International Journal of Soft Computing and Engineering (IJSCE) ISSN (2013): 2231--2307.

[14]

Ramteke, Ashwin S., and Milind E. Rane. "Offline handwritten devanagari script segmentation." international Journal Of Scientific & Technology Research 1.4 (2012).

[15]

Rani, Vneeta, and Pankaj Kumar. "Problems of character segmentation in Handwritten Text Documents written in Devnagari Script." International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) 2.3 (2013): pp-1026.

[16]

Dongre, Vikas J., and Vijay H. Mankar. "Devnagari document segmentation using histogram approach." arXiv preprint arXiv:1109.1247 (2011).

Cited By

Habib SShukla MKapoor R(2021)A Comparative Study on Recognition of Degraded Urdu and Devanagari Printed DocumentsProceedings of International Conference on Machine Intelligence and Data Science Applications10.1007/978-981-33-4087-9_31(357-368)Online publication date: 8-May-2021
https://doi.org/10.1007/978-981-33-4087-9_31
Narang SJindal MKumar M(2019)Drop flow method: an iterative algorithm for complete segmentation of Devanagari ancient manuscriptsMultimedia Tools and Applications10.1007/s11042-019-7620-678:16(23255-23280)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1007/s11042-019-7620-6

Touching character segmentation of Devanagari script
1. Applied computing
  1. Document management and text processing
    1. Document capture
2. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
  2. Computer graphics

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ICCCNT '16: Proceedings of the 7th International Conference on Computing Communication and Networking Technologies

July 2016

262 pages

ISBN:9781450341790

DOI:10.1145/2967878

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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University of North Texas: University of North Texas

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Association for Computing Machinery

New York, NY, United States

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Published: 06 July 2016

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ICCCNT '16

ICCCNT '16: 7th International Conference on Computing Communication and Networking Technologies

July 6 - 8, 2016

TX, Dallas, USA

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ICCCNT '16 Paper Acceptance Rate 48 of 101 submissions, 48%;

Overall Acceptance Rate 48 of 101 submissions, 48%

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Cited By

Habib SShukla MKapoor R(2021)A Comparative Study on Recognition of Degraded Urdu and Devanagari Printed DocumentsProceedings of International Conference on Machine Intelligence and Data Science Applications10.1007/978-981-33-4087-9_31(357-368)Online publication date: 8-May-2021
https://doi.org/10.1007/978-981-33-4087-9_31
Narang SJindal MKumar M(2019)Drop flow method: an iterative algorithm for complete segmentation of Devanagari ancient manuscriptsMultimedia Tools and Applications10.1007/s11042-019-7620-678:16(23255-23280)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1007/s11042-019-7620-6

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