Forgery Detection and Value Identification of Euro Banknotes

Bruna, Arcangelo; Farinella, Giovanni Maria; Guarnera, Giuseppe Claudio; Battiato, Sebastiano

doi:10.3390/s130202515

Cited by 45 publications

(18 citation statements)

References 14 publications

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“…In paper [9] the author proposed an effective system to detect counterfeit currency notes by processing the image of currency note taken by IR camera which is illuminated by IR led. By testing 1750 banknotes have attained 95.7% efficiency.…”

Section: Second Line Inspection Methods A) Counterfeit Detection Penmentioning

confidence: 99%

CHALLENGES IN INDIAN CURRENCY DENOMINATION RECOGNITION & AUTHENTICATION

Ali¹,

Mukherjee²

2014

IJRET

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Automatic currency recognition and authentication has become an impending challenge today particularly because of the prevailing fraudulent activities as it hampers our economy. According to the RBI report 435,607 fake notes has been detected in year 2010-2011 and the number is only increasing with technological advancements in the field of printing. Image processing techniques such as texture based, pattern or color based, character recognition etc using different operator or tools such as Prewitt or Sobel or Canny edge detector, ANN, heuristic analysis, SVM etc are commonly used for recognition and authentication of paper currency note. Despite several researches it still remains an open challenge. This paper intends to present an extensive survey of the recent technological trends in recognition and authentication of paper currency note while identifying the various challenges.

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Section: Second Line Inspection Methods A) Counterfeit Detection Penmentioning

confidence: 99%

CHALLENGES IN INDIAN CURRENCY DENOMINATION RECOGNITION & AUTHENTICATION

Ali¹,

Mukherjee²

2014

IJRET

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show abstract

“…The recognition rate of the algorithm is true for 100% and false for 0%. Bruna et al [15] have proposed the system that detects the counterfeit of euro banknotes and calculate its performance based on speed and accuracy. Feng et al [16] have also proposed a new system for identification of Renminbi Banknote (RMB) character from RMB images with two different methods namely skew correction and orientation identification.…”

Section: Related Workmentioning

confidence: 99%

An Efficient Technique for Detection of Fake Currency

Snehlata¹,

Saxena²

2019

IJRTE

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During the past years, some of the researchers are using the matching techniques for identification of the fake currency either by using the Mathematical formulation or by using the readymade simulation tools. A lot of methods namely edge detection, segmentation, feature extraction, pattern matching has been used for finding and identification of the fake currency. In the present work, Principal Component Analysis (PCA) is used to detect the feature of currency through modeling and a proposed algorithm is elaborated to recognize the fake currency in the form of note Rs 2000 of Indian currency. Graphs are also designed to justify the present approach along with the comparison of results

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“…The system has been tested and validated on a dataset provided by Italy's central bank. [25] Report depicts the result of counterfeit detection from 2006-2008, currency management operations conducted by RBI and also the steps taken by RBI to restraint currency counterfeiting. Consequently, it can be illustrated that even after Zero tolerance policy for counterfeiting integrity assurance of banknotes must be effectively improved and for this various methods, systems and solutions has been lay down.…”

Section: Related Workmentioning

confidence: 99%

Evaluating and Forecasting rate of Counterfeit Banknote Detection

Upadhyaya¹,

Shokeen²,

Srivastava³

2019

IJRTE

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Detection of counterfeit banknotes becoming a major issue in today’s scenario, as it is seems to be weighty aspect in terms of socio-economy of every living being. This paper highlights various distinguishing features of currencies of different countries, having an objective to secure their currency less susceptible from forgery. Afterwards, the paper focuses on analysing and comparing the rate of counterfeit detection with the forecasted rate of counterfeit currency detection. The analysis has been performed using, paired sample t-test and elementary time series forecasting in IBM SPSS 21 and RStudio respectively. Data points from 1999-00 to 2017-18 have been collected from Reserve Bank of India Annual reports under currency management section.

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Forgery Detection and Value Identification of Euro Banknotes

Cited by 45 publications

References 14 publications

CHALLENGES IN INDIAN CURRENCY DENOMINATION RECOGNITION & AUTHENTICATION

CHALLENGES IN INDIAN CURRENCY DENOMINATION RECOGNITION & AUTHENTICATION

An Efficient Technique for Detection of Fake Currency

Evaluating and Forecasting rate of Counterfeit Banknote Detection

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