Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{179094,
        author = {Vedha Vidhya S L and Sharmila S and Baseetha S M and Sathishkumar J S and Geetha G},
        title = {AI-DRIVEN OCR AND FACIAL LANDMARK-BASED LIVENESS DETECTION FOR AADHAAR VERIFICATION FOR GOVERNMENT SECTOR},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {5884-5886},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179094},
        abstract = {This project introduces an intelligent, automated system designed to streamline the processing of loan applications by integrating Optical Character Recognition (OCR), Natural Language Processing (NLP), and Flask-based web development. Users can complete a digital loan application form and upload their Aadhaar card as a supporting document. Upon submission, Tesseract OCR is employed to extract key information such as the applicant’s name and address from the uploaded Aadhaar card. Using NLP techniques and regular expressions, the extracted data is cleaned and refined to accurately isolate relevant details, which are then cross-verified against the information provided by the user to ensure authenticity. The verified data is systematically organized and compiled into a downloadable PDF report for documentation purposes. Additionally, geolocation services are incorporated to validate address details using GPS coordinates, adding an extra layer of verification. The entire system enables faster processing, minimizes human error, and strengthens data verification through fuzzy matching and location-based intelligence. This project showcases how AI-driven document automation can significantly optimize financial workflows and enhance the reliability of loan application procedures. The platform is built to be scalable, secure, and adaptable, making it highly suitable for a wide range of digital verification applications, especially in fintech and e-governance domains.},
        keywords = {OCR, NLP, Fuzzy Matching, GPS based address verification, Flask web application},
        month = {May},
        }