Deciphering Ancient Tamil Epigraphy: A Deep Learning Approach for Vatteluttu Script Recognition

  • R. Vijaya Arjunan
  • , Ruppikha Sree Shankar
  • , Manjunath G. Asuti
  • , Nirmalkumar S. Benni
  • , Nijaguna Gollara Siddappa
  • , Praveen S. Challagidad
  • , Venkatesh Bhandage*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

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 languageEnglish
Pages (from-to)451-467
Number of pages17
JournalJournal of Internet Services and Information Security
Volume15
Issue number1
DOIs
Publication statusPublished - 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

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