Publication Date: 2023/05/06
Abstract: - The printing and scanning industry has made significant technological advancements, but unfortunately, thishas also led to a rise in counterfeiting. Counterfeit currency cannegatively impact the economy and reduce the value of genuine money. Therefore, detecting fake currency is crucial. Traditional methods have relied on hardware and image processing techniques, which can be inefficient and timeconsuming. To address this issue, we have proposed a new approach that uses a deep convolutional neural network to detect counterfeit currency. Our method analyzes currency images and can efficiently identify fake currency in real time. We trained a transfer learned convolutional neural network using a dataset of two thousand currency notes to learn the feature map of genuine currency. Once the feature map islearned, the network is able to identify counterfeit currency quickly and accurately. Our proposed approach is highly effective and significantly reduces the time required to identify fake currency among the 500 notes in our dataset.
Keywords: No Keywords Available
DOI: https://doi.org/10.5281/zenodo.7902617
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23APR1823.pdf
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