Nigerian Naira Note Counterfeit Detection

This study provided a technique for easy and inexpensive authentication of Nigerian naira notes. The system allowed for the input of naira notes across all denominations and in any position. In this paper, we focused exclusively on paper notes. The suggested approach isolated the watermark region in the note and checked its validity. Ideally, the picture of the note would be taken using backlighting while positioned on the backlight. The proposed method successfully isolated and authenticated four denominations of the Nigerian naira: 1000, 500, 200, and 100. This technique provided near-certainty authentication for these naira notes, offering an efficient and scalable solution for counterfeit detection.

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Publication Details

Journal
International Journal of Emerging Technology and Advanced Engineering
Published
2025-06-22
DOI
https://doi.org/10.46338/ijetae0625_01
Primary Topic
Biometric Identification and Security
Type
article
Field-Weighted Citation Impact
0.00
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article

Nigerian Naira Note Counterfeit Detection

Amazue Uchenna, Osadebe Chijioke, Ilonze Chibuikem
International Journal of Emerging Technology and Advanced Engineering
Biometric Identification and Security
article

Nigerian Naira Note Counterfeit Detection

Amazue Uchenna, Osadebe Chijioke, Ilonze Chibuikem
article en

Abstract

This study provided a technique for easy and inexpensive authentication of Nigerian naira notes. The system allowed for the input of naira notes across all denominations and in any position. In this paper, we focused exclusively on paper notes. The suggested approach isolated the watermark region in the note and checked its validity. Ideally, the picture of the note would be taken using backlighting while positioned on the backlight. The proposed method successfully isolated and authenticated four denominations of the Nigerian naira: 1000, 500, 200, and 100. This technique provided near-certainty authentication for these naira notes, offering an efficient and scalable solution for counterfeit detection.

International Journal of Emerging Technology and Advanced EngineeringVol. 15(6)
Openalex Percentile: Top 83%
Biometric Identification and Security
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