Paper Key : IRJ************557
Author: Giribabu Ruppa,Annam Brundavani,Rachapudi Vinod, Telukala Usharanisahu,Vadada Yamuna
Date Published: 15 Apr 2024
Abstract
The Indian economy suffers greatly from counterfeit money. The integrity of the Indian economy must be preserved. The development of color printing technology has led to a significant rise in the production and large-scale replication of counterfeit banknotes. It is quite hard to tell what is false from what is true. Because people differentiate based on outward appearance, it becomes impossible for common individuals to tell whether the money is real or phony. We're using a smart computer system called a Convolutional Neural Network (CNN) using YOLO V5 algorithm. We trained this system using a bunch of pictures containing real and fake money of different types. The dataset is pre-processed by resizing images to a uniform size and normalizing pixel values, optimizing them for CNN analysis. The preprocessed images are then split into training and validation sets for training and testing the model, respectively. Keywords: Indian currency, YOLO, Convolutional Neural Network, Recognition, Features of note.