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

该研究训练和分析应用于位于 Brihadeeswarar Temple 墙壁上发现的 10 世纪古代泰米尔铭文的光学字符识别（OCR）方法，其中选择的 OCR 方法包括使用现代 ICR 技术预处理原始数据的 Tesseract（一种广泛使用的 OCR 引擎）和一个框编辑软件来调优我们的模型，通过 Tesseract 的分析来评估它们在准确解读古代泰米尔字符方面的有效性，我们的模型在数据集上的性能通过准确率来确定，该数据集被划分为训练集和测试集，通过解决脚本的历史背景所带来的独特挑战，该研究旨在为 OCR 领域的改进保存和解释古代铭文做出有价值的贡献。