Software system to detect counterfeit Egyptian currency

Shoeb, Abdullah M.; Sayed, Hadeer M.; Saleh, Norah F.; Khafagy, Ehab I.; Neji, S.

doi:10.1109/iccicct.2016.7988010

Cited by 3 publications

(1 citation statement)

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“…In comparison, our proposed solution does use an enclosure to ensure uniform illumination across all processed training and validation images. Publications such as [5] and [6] that are based on digital image processing techniques have some flaws, as they did not consider the use of supervised learning algorithms to solve the classification task. On the contrary, our proposed solution uses a support vector machine (SVM) to tackle the classification problem after a training process performed with labeled images.…”

Section: Literature Reviewmentioning

confidence: 99%

An algorithm for Peruvian counterfeit Banknote Detection based on Digital Image Processing and SVM

Huaytalla¹,

Humari²,

Kemper³

2021

Adv. sci. technol. eng. syst. j.

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In this work we propose an algorithm for Peruvian counterfeit banknotes detection. Our algorithm operates in banknotes with 50, 100 and 200 soles denominations that were manufactured from 2009 onwards. This algorithm offers an automatic diagnosis based on digital image processing and support vector machines (SVM). Current Peruvian counterfeit detection systems are specially designed to analyze relevant characteristics in dollars and euros. Then, some counterfeiters can fool these systems. We made our detection system robust because we focus on the image acquisition and the segmentation of intaglio marks engraved over the banknotes. After segmentation, we applied embossing and Sobel filters followed by an aperture morphological operation to obtain special characteristics that were then classified by an SVM. We have validated our methodology using real and fake banknotes from a dataset of 240 samples provided by Central Reserve Bank of Peru (BCRP). Our final identification accuracy was 96.5%.

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Section: Literature Reviewmentioning

confidence: 99%

An algorithm for Peruvian counterfeit Banknote Detection based on Digital Image Processing and SVM

Huaytalla¹,

Humari²,

Kemper³

2021

Adv. sci. technol. eng. syst. j.

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Banknote identification based on characteristic differences

Nagayoshi,

Hiramatsu,

Fujimura

et al. 2024

Elect Comm in Japan

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A method for banknote identification has been developed. As a prerequisite for this process, an ATM stores records captured from accepted banknotes, including customer's information for identification. The proposed method is implemented when a counterfeit banknote is detected. The ATM identifies a record corresponding to the counterfeit banknote among the stored records, assisting in the identification of the customer who used it. This identification is carried out by exploiting characteristic differences between counterfeit and genuine banknotes. These differences are defined in terms of positions and magnitudes of variations. An experiment using simulated banknotes was conducted to assess the effectiveness of the proposed method. Additionally, another experiment involving digitally synthesized banknotes was conducted to determine the performance limits of the proposed method.

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