Authors :
Suhaylah Sajid
Volume/Issue :
Volume 9 - 2024, Issue 10 - October
Google Scholar :
https://tinyurl.com/yeys8eba
Scribd :
https://tinyurl.com/bdhnpkh5
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24OCT1896
Abstract :
Fakes are a major threat to India’s economy
hence the need for a solution that will help detect these
materials easily and accurately. The detection of
counterfeit currency is a major concern for almost all
countries, and this research focuses on developing a
MATLAB-based counterfeit currency detection system
which evaluates a true image of the Indian Currencies
with the help of image processing and pattern recognition
technique. Benefiting from MATLAB’s powerful image
processing resources, the system conducts the necessary
preprocessing, feature extraction and classification of
vital security elements of currency, such as watermarks,
security threads and micro-lettering which play an
important role in identifying the genuine currency from
the counterfeit. The specific characteristics of edge and
texture are statistically and geometrically calculated, and
the normal and high-resolution light conditions are at
high accuracy with varying resolutions. In order to
determine a distinction between actual and fake notes,
support vector machine (SVM) classifiers are used. By
validating this MATLAB solution, it has been determined
to be effective as an easy to use, robust and customizable
software that has the potential to work in numerous
operations within banking and retail and prevent the
spreading of counterfeit money.
Keywords :
Counterfeit Currency Detection, Indian Currency, MATLAB, Image Processing, Pattern Recognition, Feature Extraction, Support Vector Machine (SVM), Statistical Features, Edge Detection, Texture Analysis, Machine Learning, Real-Time Detection.
References :
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- S. Gupta and N. Agarwal, “A review on counterfeit currency detection techniques using image processing,” *Int. J. Sci. Eng. Res.*, vol. 2021, 2021.
- P. Patel and A. Jain, “Fake currency detection using image processing techniques,” *2021 Int. Conf. Intell. Comput. Control Syst. (ICICCS)*, 2021.
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- P. D. Deshpande and A. Shrivastava, “Indian Currency Recognition and Authentication using Image Processing,” *Int. J. Adv. Res. Sci. Eng.*, vol. 7, no. 7, pp. 1107-1119, 2018.
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- A. Jain and A. Kumar, “Detection of fake Indian currency notes using image processing techniques,” *2017 Int. Conf. Innov. Inf. Embed. Commun. Syst. (ICIIECS)*, 2017.
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- S. Puri, A. Bhardwaj, and R. Sharma, et al., “Currency Recognition System using Image Processing Techniques,” *Int. J. Comput. Appl.*, vol. 55, no. 4, 2012.
- L. Liu and Y. Lu, “An Image-Based Approach to Detection of Fake Coins,” *Trans. Inf. Syst.*, June 2011.
- N. Rathee, A. Kadian, and R. Sachdeva, “Feature Fusion for Fake Indian Currency Detection,” *2010 3rd Int. Conf. Comput. Sustain. Glob. Dev. (INDIACom)*, IEEE, 2010.
- K. Sawant and C. More, “Currency Recognition Using Image Processing and Minimum Distance Classifier Technique,” *Int. J. Adv. Eng. Res. Sci. (IJAERS)*, vol. 3, no. 3, pp. 1-8, 2009.
- S. Mahajan and K. P. Rane, “A Survey on Counterfeit Paper Currency Recognition and Detection,” *Int. Conf. Intell. Autom. Comput. (ICIAC)*, pp. 54-61, 2009.
- E. Hariri, M. Hariri, and M. Afzali, “Banknote Detection Methods and Identifying Its Imperfection,” pp. 912-918, 2008.
- H. Hassanpour, A. Yaseri, and G. Ardeshir, “Feature Extraction For Paper Currency Recognition,” *Int. Symp. Signal Process. Appl. (ISSPA)*, IEEE, 2007.
- A. Ali and M. Manzoor, “Recognition System for Pakistani Paper Currency,” *World Appl. Sci. J.*, pp. 3078-3085, 2003.
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Fakes are a major threat to India’s economy
hence the need for a solution that will help detect these
materials easily and accurately. The detection of
counterfeit currency is a major concern for almost all
countries, and this research focuses on developing a
MATLAB-based counterfeit currency detection system
which evaluates a true image of the Indian Currencies
with the help of image processing and pattern recognition
technique. Benefiting from MATLAB’s powerful image
processing resources, the system conducts the necessary
preprocessing, feature extraction and classification of
vital security elements of currency, such as watermarks,
security threads and micro-lettering which play an
important role in identifying the genuine currency from
the counterfeit. The specific characteristics of edge and
texture are statistically and geometrically calculated, and
the normal and high-resolution light conditions are at
high accuracy with varying resolutions. In order to
determine a distinction between actual and fake notes,
support vector machine (SVM) classifiers are used. By
validating this MATLAB solution, it has been determined
to be effective as an easy to use, robust and customizable
software that has the potential to work in numerous
operations within banking and retail and prevent the
spreading of counterfeit money.
Keywords :
Counterfeit Currency Detection, Indian Currency, MATLAB, Image Processing, Pattern Recognition, Feature Extraction, Support Vector Machine (SVM), Statistical Features, Edge Detection, Texture Analysis, Machine Learning, Real-Time Detection.