YOLO and OCR-Based Automated Identity Document Verification

Abstract: Ensuring the authenticity of identity documents is crucial for secure digital transactions and regulatorycompliance. This paperpresentsa Comprehensive AutomatedDocumentVerificationSystemthatutilizesYOLO (YouOnlyLookOnce)for objectdetection andOCR(Optical Character Recognition) for dataextraction toverifyAadhaar cards,PANcards, and Voter IDcards. The systemautomates the verification process by detecting key document features, extractingrelevanttextualdata, andcross-verifyingitagainst predefined templates and databases. By integrating deep learning-based object detection with OCR, the proposed solution achieves high accuracy, efficiency, and scalability, reducing reliance on manual verification and minimizing fraud risks. Experimental results demonstrate the system’s robustness in detecting forged or tampered documents. This research contributes to improving digital security and streamlining identity verification in sectors such as banking, government services, and online KYC processes.