Devi S, G., Vairavasundaram, S., Teekaraman, Y. orcid.org/0000-0003-4297-3460 et al. (2 more authors) (2022) A deep learning approach for recognizing the cursive Tamil characters in palm leaf manuscripts. Computational Intelligence and Neuroscience, 2022. 3432330. pp. 1-15. ISSN 1687-5265
Abstract
Tamil is an old Indian language with a large corpus of literature on palm leaves, and other constituents. Palm leaf manuscripts were a versatile medium for narrating medicines, literature, theatre, and other subjects. Because of the necessity for digitalization and transcription, recognizing the cursive characters found in palm leaf manuscripts remains an open problem. In this research, a unique Convolutional Neural Network (CNN) technique is utilized to train the characteristics of the palm leaf characters. By this training, CNN can classify the palm leaf characters significantly on training phase. Initially, a preprocessing technique to remove noise in the input image is done through morphological operations. Text Line Slicing segmentation scheme is used to segment the palm leaf characters. In feature processing, there are some major steps used in this study, which include text line spacing, spacing without obstacle, and spacing with an obstacle. Finally, the extracted cursive characters are given as input to the CNN technique for final classification. The experiments are carried out with collected cursive Tamil palm leaf manuscripts to validate the performance of the proposed CNN with existing deep learning techniques in terms of accuracy, precision, recall, etc. The results proved that the proposed network achieved 94% of accuracy, where existing ResNet achieved 88% of accuracy.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2022 The Authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Deep Learning; Humans; India; Language; Neural Networks, Computer; Plant Leaves |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 14 Apr 2022 10:34 |
Last Modified: | 14 Apr 2022 10:34 |
Status: | Published |
Publisher: | Hindawi Limited |
Refereed: | Yes |
Identification Number: | 10.1155/2022/3432330 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:185710 |