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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 117
Article Submitted : 21318
Article Published : 8476
Total Authors : 22301
Total Reviewer : 802
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| Paper Title: | Counterfiet Currency detection using machine learning |
| Authors Name: | Siri S , Deekshitha S , Jeevan CB |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_208412
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| Published Paper Id: | IJRTI2512067 |
| Published In: | Volume 10 Issue 12, December-2025 |
| DOI: | |
| Abstract: | Counterfeit currency poses a major threat to financial stability across countries such as India, the United States, and Europe. Traditional verification methods are often unreliable because modern counterfeit notes closely replicate genuine banknote features, making manual inspection difficult and error-prone. This paper presents Currency Authenticator AI, an automated multi-currency counterfeit detection system that analyzes banknote images captured through a webcam or uploaded by the user. The proposed model utilizes a hybrid pipeline that combines classical image-processing techniques with a Convolutional Neural Network (CNN) to examine key security elements including microtext, watermark intensity, serial number format, color patterns, security threads, and hologram regions. The system provides both a real/fake prediction and a detailed, feature-level explanation of the results. Experimental evaluation on multiple international currencies demonstrates strong accuracy and consistent performance under varied lighting and capture conditions. The system’s real-time capability and user-friendly interface make it practical for everyday use in banks, retail environments, and public verification platforms. Overall, the study highlights the effectiveness of integrating AI-driven models for reliable and accessible counterfeit currency authentication. |
| Keywords: | Counterfeit Currency Detection Fake Currency Identification Machine Learning Deep Learning Convolutional Neural Network (CNN) Image Processing Banknote Authentication Multi-Currency Verification Security Feature Analysis Real-Time Currency Detection |
| Cite Article: | "Counterfiet Currency detection using machine learning", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 12, page no.a540-a544, December-2025, Available :http://www.ijrti.org/papers/IJRTI2512067.pdf |
| Downloads: | 000183 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2512067
Registration ID:208412
Published In: Volume 10 Issue 12, December-2025
DOI (Digital Object Identifier):
Page No: a540-a544 Country: Bangalore Urban, Karnataka, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2512067 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2512067 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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