Abstract
Vatteluttu (Vattezhuthu) script, prevalent between the 3rd and 8th century CE, played a crucial role in documenting early Chola and Pandya history. However, despite its historical significance, thousands of inscriptions remain untranslated, hindering a comprehensive understanding of early South Indian heritage. This research addresses these challenges by developing a deep learning-based approach for digitizing and recognizing Vatteluttu characters. Using a dataset of 1,800 segmented images representing 28 characters, the study integrates advanced preprocessing techniques and a Siamese CNN-RNN architecture to classify ancient scripts with an overall accuracy of 98%. The findings demonstrate the feasibility of automated transcription for ancient scripts, offering a robust framework for preserving and enhancing research on South Indian heritage.
| Original language | English |
|---|---|
| Pages (from-to) | 451-467 |
| Number of pages | 17 |
| Journal | Journal of Internet Services and Information Security |
| Volume | 15 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 01-02-2025 |
All Science Journal Classification (ASJC) codes
- Computer Science (miscellaneous)
- Software
- Information Systems
- Computer Science Applications
- Computer Networks and Communications
- Electrical and Electronic Engineering