Automatic Interpretation and Digitization of Ancient Indian Scripts using Image Processing and Deep Learning

Abstract

Ancient Indian knowledge preservation is frequently hampered by brittle manuscripts, faded inscriptions, and unreadable script types. The difficulties in manually deciphering and digitizing these documents have resulted in their underutilization, despite their enormous cultural and historical significance. This study offers a method for automatically identifying and restoring ancient Indian characters that is based on deep learning and image processing. The suggested system integrates neural networks for precise character detection and script classification and computer vision techniques to improve damaged or low-quality manuscripts. Additionally, generative models are used to rebuild parts that are unclear or missing, allowing for more comprehensive digital archives. The goal of this research is to develop a scalable and effective method for preserving India's cultural legacy by fusing cutting-edge artificial intelligence with conventional script analysis. By making old texts searchable, accessible, and available for further study, the results should benefit linguists, historians, and digital libraries.

DOI: https://doi.org/10.24321/3051.424X.202406