Detection of Counterfeit Currency Notes Through Machine Learning Algorithms and Image Processing

Shokeen, Vikrant; Kumar, Sandeep; Sharma, Amit; Singh, Neha; Prasad, Aman; Sachdeva, Yugank

doi:10.1109/ictacs59847.2023.10390478

2023 3rd International Conference on Technological Advancements in Computational Sciences (ICTACS) 2023

DOI: 10.1109/ictacs59847.2023.10390478

|View full text |Cite

Detection of Counterfeit Currency Notes Through Machine Learning Algorithms and Image Processing

Vikrant Shokeen,

Sandeep Kumar,

Amit Sharma

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Counterfeit Currency Detection Using Machine Learning

Mrs. Sonali B. Kanawade,

Sammed S. Jangade,

Abhishek R. Mane

et al. 2024

Int J Sci Res Sci Eng Technol

View full text Add to dashboard Cite

Counterfeit currency detection is a critical aspect of maintaining financial integrity. This paper introduces an innovative methodology for identifying counterfeit Indian rupee notes. By employing advanced image processing techniques and Convolutional Neural Networks (CNNs), specifically ResNet architecture, the proposed system achieves impressive accuracy in distinguishing genuine from counterfeit banknotes. The dataset, meticulously compiled through a combination of web scraping and synthetic printing, ensures robust training and evaluation. Experimental findings underscore the efficacy of the ResNet-based approach, highlighting its superiority over traditional CNN models. This research contributes significantly to bolstering currency security and trust in financial transactions, offering practical insights for combating counterfeit currency challenges.

show abstract

Counterfeit Currency Detection Using Machine Learning

Mrs. Sonali B. Kanawade,

Sammed S. Jangade,

Abhishek R. Mane

et al. 2024

Int J Sci Res Sci Eng Technol

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Detection of Counterfeit Currency Notes Through Machine Learning Algorithms and Image Processing

Cited by 1 publication

References 17 publications

Counterfeit Currency Detection Using Machine Learning

Counterfeit Currency Detection Using Machine Learning

Contact Info

Product

Resources

About