Image Based Character Recognition, Documentation System To Decode Inscription From Temple
This work addresses the problem of preserving and interpreting ancient inscriptions for historians and archaeologists, but it is incremental as it uses existing methods on new data.
The project applied Tesseract OCR with preprocessing techniques to decode 10th-century ancient Tamil inscriptions from a temple, achieving an accuracy rate evaluated on a training and testing dataset.
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