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Tamil Handwritten Character Recognition: A Comprehensive Review of Recent Innovations and Progress
International Journal of Advanced Computer Science and Applications(IJACSA), Volume 16 Issue 8, 2025.
Abstract: Recognizing handwritten characters is a complex task, particularly when dealing with Tamil, a writing system known for its intricate and stylized nature. Several challenges arise in recognizing Tamil handwritten characters, including the complexity of the writing style, similar character shapes, irregular handwriting, slanting characters, varying curves, inconsistent font sizes, and limited datasets. Additionally, the diversity of writing styles and the absence of a standard solution for accurately recognizing all Tamil characters further complicate the process. To address these issues, researchers have explored various techniques, including neural networks, support vector machines, clustering, and groupwise classification. However, Tamil handwritten character recognition remains an evolving field with ample opportunities for exploration and advancement. This review study aims to provide a thorough analysis of the current state of the field, identify key challenges, and highlight areas for improvement. Furthermore, it presents a detailed examination of the proposed techniques and suggests potential directions for future research in this domain.
Keywords: Convolutional Neural Network (CNN); handwritten recognition; Tamil characters; offline recognition; feature extraction techniques; neural network architecture; Support Vector Machine (SVM); groupwise classification
Manoj K and Iyapparaja M. “Tamil Handwritten Character Recognition: A Comprehensive Review of Recent Innovations and Progress”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.8 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0160831
@article{K2025,
title = {Tamil Handwritten Character Recognition: A Comprehensive Review of Recent Innovations and Progress},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160831},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160831},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {8},
author = {Manoj K and Iyapparaja M}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
