The Role of Artificial Intelligence and Pattern Recognition in the Authentication and Analysis of Historical Documents: A Literature Review

This systematic literature review explores the application of artificial intelligence (AI) and pattern recognition techniques in the authentication and analysis of historical documents. A comprehensive search strategy across three major academic databases (Scopus, IEEE Xplore, and ACM Digital Library) yielded 17 relevant studies published between 2007 and 2023. The selected studies demonstrate the potential of various AI techniques, including deep learning approaches, natural language processing, and unsupervised learning methods, for tasks such as handwritten text recognition, document restoration, and visual similarity clustering. The reviewed literature highlights successful applications in digital preservation, automatic transcription, and information extraction, showcasing the ability of AI and pattern recognition to automate and accelerate the processing of large collections of historical documents. However, challenges such as the scarcity of annotated datasets, the need for interdisciplinary collaboration, and the development of user-friendly interfaces remain important areas for future research and development. This review emphasizes the significance of collaborative and interdisciplinary efforts in addressing these challenges and unlocking the potential of AI and pattern recognition in preserving and studying our cultural heritage contained within historical documents.