• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology


Indian Journal of Science and Technology

Year: 2023, Volume: 16, Issue: 26, Pages: 1935-1946

Original Article

Review of Character Recognition Techniques for MODI Script

Received Date:04 March 2023, Accepted Date:06 May 2023, Published Date:04 July 2023


Objectives: The main objective of this study is to review and compare the various methods used for Modi script recognition. Methods: The author has chosen various methods from 2010 to 2022 that are used to process MODI Script. The distinct methods employed for feature extraction and classification are compared for various datasets. A discussion on the significance of the selection of correct feature extraction and classification techniques and the comments on the methods suited to specific applications is provided. Findings: Currently, there are very few MODI translators. In contrast, millions of historical documents written in MODI remain unexplored. Novelty: The Convolutional Neural Networks (CNNs) has been used successfully for recognizing MODI Script characters. In the present study the author finds that, compared to all techniques, CNN provides maximum accuracy of 99.78%. Hence, CNN is the best character recognition technique for the MODI script.

Keywords: Distance Classifier; Feature Extraction; and Classification; Handwritten Characters; MODI Lipi; Character Recognition


  1. Chandankhede C, Sachdeo R. Offline MODI script character recognition using deep learning techniques. Multimedia Tools and Applications. 2023;82(14):21045–21056. Available from: https://doi.org/10.1007/s11042-023-14476-0
  2. Deshmukh M, Patil M, Kohle S. The Divide-and-Conquer based algorithm to detect and correct the skew angle in the old age historical handwritten MODI lipi documents. International Journal of Computer Science and Applications. 2017;14(2):47–63. Available from: https://apps.nmu.ac.in/naac/0/3/all/345/427.pdf
  3. Chandure S, Inamdar V. Offline Handwritten MODI Character Recognition Using GoogLeNet and AlexNet. 2021 The 13th International Conference on Computer Modeling and Simulation. 2021. Available from: https://doi.org/10.1145/3474963.3474974
  4. Jadhav S, Inamdar V. Convolutional Neural Network and Histogram of Oriented Gradient Based Invariant Handwritten MODI Character Recognition. Pattern Recognition and Image Analysis. 2022;32(2):402–418. Available from: https://doi.org/10.1134/S1054661822020109
  5. Joseph S, Datta A, Anto O, Philip S, George J. OCR System Framework for MODI Scripts using Data Augmentation and Convolutional Neural Network. Data Science and Security. 2021;p. 201–209. Available from: https://doi.org/10.1007/978-981-15-5309-7_21
  6. Pawar V, Wadkar D, Kashid S, Prakare P, More V, Babar A. MODI Lipi Handwritten character Recognition using CNN and Data Augmentation Techniques. International Research Journal of Engineering and Technology. 2022;p. 1880–1884. Available from: https://www.irjet.net/archives/V9/i6/IRJET-V9I6337.pdf
  7. Das S, Wankhede K, Rituraj A. Review on Modi Handwritten Characters Recognition. International Research Journal of Modernization in Engineering Technology and Science. 2022;(11) 1267–1274. Available from: https://www.irjmets.com/uploadedfiles/paper/issue_11_november_2022/31334/final/fin_irjmets1668970066.pdf
  8. Joseph S, George J. Efficient Handwritten Character Recognition of MODI Script Using Wavelet Transform and SVD. Data Science and Security. 2021;p. 227–233. Available from: https://doi.org/10.1007/978-981-15-5309-7_24
  9. Joseph S, George J. Data Augmentation for Handwritten Character Recognition of MODI Script Using Deep Learning Method. Information and Communication Technology for Intelligent Systems. 2021;p. 515–522. Available from: https://doi.org/10.1007/978-981-15-7062-9_51
  10. Joseph S, George J. Handwritten Character Recognition of MODI Script using Convolutional Neural Network Based Feature Extraction Method and Support Vector Machine Classifier. 2020 IEEE 5th International Conference on Signal and Image Processing (ICSIP). 2020;2020. Available from: https://doi.org/10.1109/ICSIP49896.2020.9339435
  11. Tamhankar PA, Masalkar KD, Kolhe SR. Character Recognition of Offline Handwritten Marathi Documents Written in MODI Script Using Deep Learning Convolutional Neural Network Model. Communications in Computer and Information Science. 2021;p. 478–487. Available from: https://doi.org/10.1007/978-981-16-0507-9_40
  12. Shah R, Gupta MK, Kumar A. Line Level Modi (Heritage script) OCR using Attention based Encoder-Decoder Architecture. 2021 Sixth International Conference on Image Information Processing (ICIIP). 2021;p. 273–278. Available from: https://doi.org/10.1109/ICIIP53038.2021.9702605
  13. Tamhankar PA, Masalkar KD, Kolhe SR. A Novel Approach for Character Segmentation of Offline Handwritten Marathi Documents written in MODI Script. Procedia Computer Science. 2020;171:179–187. Available from: https://doi.org/10.1016/j.procs.2020.04.019
  14. Shekhar C. Designing a New Digital Font for Modi - Script. Ergonomics International Journal. 2018;2(4). Available from: https://medwinpublishers.com/EOIJ/EOIJ16000150.pdf
  15. Nilesh K, Pundlikrao N. Transliteration of Indian Ancient Script to Braille Script using Pattern Recognition Technique: A Review. International Journal of Computer Applications. 2017;166(6):33–38. Available from: https://doi.org/10.5120/ijca2017914162
  16. Kulkarni SA, Yannawar PL. Recognition of Partial Handwritten MODI Characters Using Zoning. Communications in Computer and Information Science. 2021;p. 407–430. Available from: https://doi.org/10.1007/978-981-16-0507-9_35
  17. Solanki B, Ingle M. Performance Evaluation of Thresholding Techniques on Modi Script. 2018 International Conference on Advanced Computation and Telecommunication (ICACAT). 2018;p. 1–6. Available from: https://doi.org/10.1109/ICACAT.2018.8933594
  18. Deshmukh MS, Patil MP, Kolhe SR. A hybrid text line segmentation approach for the ancient handwritten unconstrained freestyle Modi script documents. The Imaging Science Journal. 2018;66(7):433–442. Available from: https://doi.org/10.1080/13682199.2018.1499226
  19. Maurya RK, Maurya SR. Recognition of a Medieval Indic-Modi Script using Empirically Determined Heuristics in Hybrid Feature Space. International Journal of Computer Sciences and Engineering. 2018;6(2):136–142. Available from: https://www.ijcseonline.org/pub_paper/19-IJCSE-02860.pdf
  20. Patil PA. Character Recognition System for Modi Script. International Journal of Computational Engineering Research. 2016. Available from: http://www.ijceronline.com/papers/Vol6_issue9/F0609031038.pdf
  21. Chandure SL, Inamdar V. Performance analysis of handwritten Devnagari and MODI Character Recognition system. 2016 International Conference on Computing, Analytics and Security Trends (CAST). 2016;p. 513–516. Available from: https://doi.org/10.1109/CAST.2016.7915022
  22. Sadanand AK, Prashant LB, Ramesh RM, Pravin LY. Offline MODI Character Recognition Using Complex Moments. Procedia Computer Science. 2015;58:516–523. Available from: https://doi.org/10.1016/j.procs.2015.08.067
  23. Kulkarni S, Borde P, Manza R, Yannawar P. Recognition of Handwritten MODI Numerals using Hu and Zernike features. CoRR. 2014;1:1–7. Available from: https://arxiv.org/vc/arxiv/papers/1404/1404.1151v1.pdf
  24. Besekar DN. Special Approach for Recognition of Handwritten MODI Script’s Vowels. Proceedings published by International Journal of Computer Applications® (IJCA). 2012;p. 48–52. Available from: https://research.ijcaonline.org/medha/number1/medha1023.pdf
  25. Gharde SS, Ramteke RJ. Recognition of characters in Indian MODI script. 2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC). 2016;p. 236–240. Available from: https://doi.org/10.1109/ICGTSPICC.2016.7955304
  26. Joseph S, George JP, Gaikwad S. Character Recognition of MODI Script Using Distance Classifier Algorithms. ICT Analysis and Applications. 2020;p. 105–113. Available from: https://doi.org/10.1007/978-981-15-0630-7_11
  27. Joseph S, George JP. Offline Character Recognition of Handwritten MODI Script Using Wavelet Transform and Decision Tree Classifier. Information and Communication Technology for Competitive Strategies (ICTCS 2020). 2022;p. 509–517. Available from: https://doi.org/10.1007/978-981-16-0739-4_48
  28. Sadanand AK, Prashant LB, Ramesh RM, Pravin LY. Impact of zoning on Zernike moments for handwritten MODI character recognition. 2015 International Conference on Computer, Communication and Control (IC4). 2015;4. Available from: https://doi.org/10.1109/IC4.2015.7375516
  29. Sawant S, Sharma A, Suvarna G, Tanna T, Kulkarni S. Word Transcription of MODI Script to Devanagari Using Deep Neural Network. 2020 3rd International Conference on Communication System, Computing and IT Applications (CSCITA). 2020. Available from: https://doi.org/10.1109/CSCITA47329.2020.9137781


© 2023 Varpe & Sakhare. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)


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