Recognition of Fake Currency Note using Convolutional Neural Networks
Navya Krishna G1, Sai Pooja G2, Naga Sri Ram B3, Yamini Radha V4, Rajarajeswari P5
1Navya Krishna G, Department of CSE, Koneru Lakshmaiah Education Foundation, Guntur (A.P), India.
2Sai Pooja G, Department of CSE, Koneru Lakshmaiah Education Foundation, Guntur (A.P), India.
3Naga Sri Ram B, Department of CSE, Koneru Lakshmaiah Education Foundation, Guntur (A.P), India.
4Yamini Radha V, Department of CSE, Koneru Lakshmaiah Education Foundation, Guntur (A.P), India.
5Rajarajeswari P, Department of CSE, Koneru Lakshmaiah Education Foundation, Guntur (A.P), India.
Manuscript received on 07 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 58-63 | Volume-8 Issue-5, March 2019 | Retrieval Number: E2857038519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper, the Automatic Fake Currency Recognition System (AFCRS) is designed to detect the counterfeit paper currency to check whether it is fake or original. The existing counterfeit problem due to demonetization effects the banking system and also in other fields. A new approach of Convolution Neural Network towards identification of fake currency notes through their images is examined in this paper which is comparatively better than previous image processing techniques. This method is based on Deep Learning, which has seen tremendous success in image classification tasks in recent times. This technique can help both people and machine in identifying a fake currency note in real time through an image of the same. The proposed system, AFCRS can also be deployed as an application in the smartphone which can help the society to distinguish between the fake and original currency notes. The Accuracy in the proposed system can be increased through the original fake notes, where as the proposed system contains the images from children’s bank churan label.
Keyword: Deep Learning, Convolutional Neural Network, Counterfeit Paper Currency, Automatic Recognition, Currency, Image Processing.
Scope of the Article: Neural Information Processing