• Prasad Bokare
• Sandipak Dhuri
• Pawas Gavande
• Atharva Inamdar
• Aditya Gupta

Legal document forgery is a huge threat to the integrity of institutions as well as of individuals. Based on Optical Character Recognition, NLP, and CNN, this paper designs a "Legal Document Authentication and Verification System" that targets the detection of forgery, especially at the textual, image-based, and structural layers of Indian driving license documents. It uses advanced machine learning techniques in signature, layout, and text anomaly analysis. Modular in design, with scalability features, findings have been established in governance, education, and banking sectors. Benchmarked evaluation proved promising accuracy in detecting forged documents

Forgery Detection, OCR, NLP, CNN, Deep Learning, Image Processing, Legal Document Verification.

"Legal Document Authentication and Verification System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.e393-e398, November-2024, Available :http://www.jetir.org/papers/JETIR2411442.pdf

"Legal Document Authentication and Verification System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. ppe393-e398, November-2024, Available at : http://www.jetir.org/papers/JETIR2411442.pdf