Revolutionizing Currency Security: A Yolov8-Based Approach for Automated Detection of Counterfeit Nepali Banknotes
Santosh Giri, Loknath Regmi, Sumit Yadav, Binaya Basnet, Binit KC and Mohan Bhandari*
ABSTRACT
The challenge of counterfeit currency in financial transactions requires innovative solutions for the efficient and accurate verification of banknotes. The study focuses on categorizing banknotes as fake or genuine in the context of Nepalese currency, which is crucial for maintaining economic stability, preventing financial fraud, and ensuring public trust in the monetary system. For the 180 collected samples of 1000 Nepalese rupee banknotes, the YOLOv8 algorithm achieved a true positive recall of 0.82 for the front face and 0.9863 for the back face. The mean average precision and confidence threshold achieved in the study indicate significant improvements with YOLOv8. The proposed approach demonstrates the potential for global implementation and adaptability across various hardware platforms.
