Challenges and Opportunities in Brahmi Script Recognition using Artificial Intelligence - Premanand P. Ghadekar, Tushar B. Kute (International Journal of Intelligent Systems and Applications in Engineering, 2024)
This study presents a comprehensive analysis of OCR systems specifically designed for stone inscriptions in various ancient languages. It focuses on the techniques, challenges, and advancements related to digitizing and preserving ancient texts engraved on stone. The unique characteristics of stone inscriptions, including diverse languages, ancient scripts, erosion, weathering, and non-uniform lighting conditions, are discussed. Techniques for image enhancement, feature extraction, and recognition models are investigated, with a specific emphasis on handling complexities like the Brahmi script. The research examines challenges associated with segmentation, character recognition, and the incorporation of linguistic and historical knowledge. Existing OCR frameworks, evaluation metrics, and recent advancements, such as machine learning, deep learning, and advanced imaging technologies, are presented. This study serves as a valuable resource for researchers and professionals involved in deciphering and preserving ancient stone inscriptions. It identifies opportunities for developing innovative artificial intelligence methods to enhance Brahmi script recognition for stone inscriptions, aiming to achieve better performance and improved accuracy. Promising results have not yet been achieved for OCR systems for various ancient scripts, even though several techniques have been developed So, it is possible to incorporate novel algorithmic techniques of artificial intelligence as well as suitable parameters to gain efficiency and accuracy in existing algorithms.