Legal Document Authentication and Verification System Leveraging OCR, NLP, and CNN for Comprehensive Document Authentication
Year: 2025
Type: article
Abstract: 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.
Author: Prof. Moushmee Kuri
Institution: MIT Art, Design and Technology University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4410498348