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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Utilizing Deep learning Techniques For Detecting Counterfeit Bank Currency |
| Authors Name: | Gudepu Jogesh Babu |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_220045
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| Published Paper Id: | IJNRDTH00143 |
| Published In: | Volume 9 Issue 5, May-2024 |
| DOI: | |
| Abstract: | Counterfeit Currency has always been an issue which has created a lot of problems in the market. The increasing technological advancements have made the possibility for creating more counterfeit currency which are circulated in the market which reduces the overall economy of the country. There are machines present at banks and other commercial areas to check the authenticity of the currencies. But a common man does not have access to such systems and hence a need for a software to detect fake currency arises, which can be used by common people. This proposed system uses Image Processing to detect whether the currency is genuine or counterfeit. The system is designed completely using Python programming language. It consists of the steps such as gray scale conversion, edge detection, segmentation, etc. which are performed using suitable methods. The first order and second order statistical features are extracted initially from the input and undergoes deeplearning algorithm CNN. The effective feature vectors are given to the SVM classifier unit for classification. The proposed method produced classification accuracy of 95.8 percentage. The experimental results are compared with state of-the methods and produced reliable results. |
| Keywords: | : CNN,SVM,Counterfeit currency, Technological Advancements,Image processing,Gray scale conversion,Edge detection,Segmentation,Deep learning |
| Cite Article: | "Utilizing Deep learning Techniques For Detecting Counterfeit Bank Currency", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 5, page no.297-339, May-2024, Available :http://www.ijnrd.org/papers/IJNRDTH00143.pdf |
| Downloads: | 00066 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 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:IJNRDTH00143 Registration ID: 220045 Published In: Volume 9 Issue 5, May-2024 DOI (Digital Object Identifier): Page No: 297-339 Country: visakhapatnam, Andhra Pradesh, India Research Area: Computer Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRDTH00143 Published Paper PDF: https://www.ijnrd.org/papers/IJNRDTH00143 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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