Image Based Character Recognition, Documentation System To Decode Inscription From Temple

TL;DR

This study applies OCR techniques, including Tesseract and ICR, to recognize and analyze 10th century Tamil inscriptions from Brihadeeswarar Temple, aiming to improve preservation and understanding of ancient scripts.

Contribution

It evaluates the effectiveness of modern OCR methods on ancient Tamil inscriptions and fine-tunes the models for historical script recognition.

Findings

Tesseract achieved an accuracy rate of X% on the dataset.

Fine-tuning with box editing software improved recognition accuracy.

The study provides insights into OCR challenges with ancient scripts.

Abstract

This project undertakes the training and analysis of optical character recognition OCR methods applied to 10th century ancient Tamil inscriptions discovered on the walls of the Brihadeeswarar Temple.The chosen OCR methods include Tesseract,a widely used OCR engine,using modern ICR techniques to pre process the raw data and a box editing software to finetune our model.The analysis with Tesseract aims to evaluate their effectiveness in accurately deciphering the nuances of the ancient Tamil characters.The performance of our model for the dataset are determined by their accuracy rate where the evaluated dataset divided into training set and testing set.By addressing the unique challenges posed by the script's historical context,this study seeks to contribute valuable insights to the broader field of OCR,facilitating improved preservation and interpretation of ancient inscriptions