Enhanced Counterfeit Detection of Bangladesh Currency through Convolutional Neural Networks: A Deep Learning Approach

Abhijit Pathak; Arnab Chakraborty; Minhajur Rahaman; Taiyaba Shadaka Rafa; Ummay Nayema

Abstract

Counterfeiting poses a significant threat to the stability of Bangladesh's currency, the Taka, necessitating advanced methods for detection and prevention. This paper presents an innovative approach to counterfeit detection using Convolutional Neural Networks (CNNs), a deep learning technology. Explicitly focused on Bangladesh's currency, this method aims to enhance the accuracy and efficiency of counterfeit detection by leveraging the power of artificial intelligence. The proposed approach involves training CNNs on a dataset of authentic and counterfeit Bangladeshi currency images, allowing the network to learn intricate features and patterns indicative of counterfeit notes. By exploiting the hierarchical structure of CNNs, the system can automatically extract discriminative features from currency images, enabling robust detection of counterfeit banknotes. The CNN-based approach offers several advantages compared to traditional methods, which often rely on manual inspection or rule-based algorithms. It can handle complex visual information more accurately and efficiently, making it well-suited for detecting subtle counterfeit features. Furthermore, the adaptability of CNNs allows for continuous learning and improvement, ensuring resilience against evolving counterfeit techniques. The efficacy of the proposed method is validated through extensive experimentation and evaluation, demonstrating its superior performance in detecting counterfeit Bangladesh currency notes. By harnessing the capabilities of deep learning, this approach not only enhances the security of Bangladesh's financial system but also serves as a scalable solution applicable to other currencies and regions facing similar challenges. In conclusion, the integration of Convolutional Neural Networks represents a significant advancement in counterfeit detection technology, offering a powerful and versatile tool for safeguarding the integrity of Bangladesh's currency and combating financial fraud on a global scale.

Keywords

Bangladesh Currency, Image Processing, Counterfeit Detection, Deep Learning, Machine Learning.

References

"Counterfeit Detection using Deep Learning." International Journal of Advanced Research in Science, Communication and Technology, undefined (2023). doi: 10.48175/ijarsct-9436
"Detection of Fake Currency using Machine Learning." International Journal For Science Technology And Engineering, undefined (2023). doi: 10.22214/ijraset.2023.51314
Marjuk, Ahmed, Siddiki., Md., Naimul, Hossain., Khadija, Akhter., Md., Riazur, Rahman. "Bangladeshi Currency Identification and Fraudulence Detection Using Deep Learning and Feature Extraction." International journal of computer science and mobile computing, undefined (2023). doi: 10.47760/ijcsmc.2022.v12i01.001
Homaira, Nowshin., Juel, Sikder., Utpol, Das. "A Deep Learning Approach for Detecting Bangladeshi Counterfeit Currency." undefined (2022). doi: 10.1007/978-3-031-19958-5_51
Haider, Khalil, Easa., A., A., Saber., Noor, Kaylan, Hamid., Hindren, A., Saber. "Machine learning based approach for detection of fake banknotes using support vector machine." Indonesian Journal of Electrical Engineering and Computer Science, undefined (2023). doi: 10.11591/ijeecs.v31.i2.pp1016-1022
Ali, Hasan, Md., Linkon., Md., Mahir, Labib., Faisal, Haque, Bappy., Soumik, Sarker., Marium-E-Jannat., Saiful, Islam. "Deep Learning Approach Combining Lightweight CNN Architecture with Transfer Learning: An Automatic Approach for the Detection and Recognition of Bangladeshi Banknotes." arXiv: Computer Vision and Pattern Recognition, undefined (2020).
A., Chandu, Naik. "Deep Learning Approaches for Automated Detection of Fake Indian Banknotes." undefined (2023). doi: 10.1109/ICICACS57338.2023.10100265
Mangesh, M., Ghonge., Tejas, Kachare., Manisha, Sinha., Siddharth, Kakade., Siddharth, Nigade., Sandeep, Shinde. "Real Time Fake Note Detection using Deep Convolutional Neural Network." undefined (2022). doi: 10.1109/ICCSEA54677.2022.9936084
Junfang Guo, Yanyun Zhao and Anni Cai 2010 Proc IEEE Int. Conf Network Infrastructure and Digital Content 359-363.
D. O'Loughlin, M. O'Halloran, B. M. Moloney, M. Glavin, E. Jones, and M. A. Elahi, "Microwave Breast Imaging: Clinical Advances and Remaining Challenges," IEEE Trans. Biomed. Eng., vol. 65, no. 11, pp. 2580–2590, 2018.
R. Bremananth, B. Balaji, M. Sankari and A. Ch0itra," A new approach to coin recognition using neural pattern analysis," IEEE Indicon 2005 Conference, Chennai, India, 11- 13 Dec. 2005.
Takeda F. and Omatu S., Onami S., Kadono T. and Terada K, "A Paper Currency Recognition Method by a Small Size Neural Network with Optimized Masks by GA", Proceedings of IEEE World Congress on Computational Intelligence, 1994, 42434-246.
Sanjana, Manoj Diwakar, Anand Sharma, "An Automated recognition of Fake or Destroyed Indian currency notes in Machine vision", IJCSMS, Vol. 12, April 2012.
Z. Ahmed, S. Yasmin, M. N. Islam, R. U. Ahmed, "Image processing based Feature extraction Of Bangladeshi banknotes," Proc. Software, Knowledge, Information Management and Applications (SKIMA), pp.1-8, 18-20 Dec. 2014.
[Online] http://fake currency detection. GitHub

Cites this article as

A. Pathak, A. Chakraborty, M. Rahaman, T. S. Rafa, U. Nayema, "Enhanced Counterfeit Detection of Bangladesh Currency through Convolutional Neural Networks: A Deep Learning Approach", International Journal of Innovative Research in Computer Science and Technology (IJIRCST), Vol-12, no.2, pp.10-20, 2024. Available from: https://doi.org/10.55524/ijircst.2024.12.2.2

Corresponding Author

Abhijit Pathak

Assistant Professor, Department of Computer Science and Engineering, BGC Trust University Bangladesh, Chattogram, Bangladesh

Download Full Paper

Download PDF

No. of Downloads: 72 | No. of Views: 1637

A Deep Learning Approach for Optimizing Monoclonal Antibody Production Process Parameters

Wenxuan Zheng, Mingxuan Yang, Decheng Huang, Meizhizi Jin.

November 2024 - Vol 12, Issue 6
Precision without GPS: Multi-Sensor Fusion for Autonomous Drone Navigation in Complex Environments

Siti Nur.

November 2024 - Vol 12, Issue 6
Performance Tuning in Cloud Environments: Techniques for Enhancing Application Efficiency

Abhishek Kartik Nandyala, Yuvaraj Madheswaran, Mrinal Kumar.

November 2024 - Vol 12, Issue 6

IJIRCST

Enhanced Counterfeit Detection of Bangladesh Currency through Convolutional Neural Networks: A Deep Learning Approach

Citations

Download Full Paper PDF

Total View 1637

Total Download 72