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Counterfeit fifty Ringgit Malaysian banknotes authentication using novel graph-based chemometrics method.

Nurfarhana Hassan¹, Tahir Ahmad², Naji Arafat Mahat^3,4

¹Department of Computer and Mathematical Sciences, Universiti Teknologi MARA Cawangan Pulau Pinang, Kampus Permatang Pauh, 13500, Permatang Pauh, Pulau Pinang, Malaysia.

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Summary

A new chemometrics fuzzy autocatalytic set (c-FACS) method effectively distinguishes counterfeit Malaysian banknotes. This advanced technique is faster than principal component analysis (PCA), aiding forensic investigations.

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Area of Science:

Forensic Chemistry
Chemometrics
Pattern Recognition

Background:

Banknote counterfeiting poses a significant global economic challenge.
Infrared spectroscopy is used in forensic analysis, but chemometrics are needed for discrimination.
Distinguishing genuine from counterfeit currency requires advanced analytical methods.

Purpose of the Study:

To develop and present an advanced fuzzy graph chemometrics method for banknote authentication.
To discriminate genuine from counterfeit fifty Malaysian Ringgit (RM50) banknotes.
To compare the performance of the new method against principal component analysis (PCA).

Main Methods:

Development of the chemometrics fuzzy autocatalytic set (c-FACS) technique.
Application of c-FACS for the analysis of genuine and counterfeit RM50 banknotes.
Comparative analysis with principal component analysis (PCA).

Main Results:

The c-FACS analysis revealed distinct patterns differentiating counterfeit banknotes.
The c-FACS method demonstrated faster authentication analysis compared to PCA.
c-FACS exhibited superior performance in terms of computing time.

Conclusions:

The developed c-FACS method shows significant potential in assisting investigations involving counterfeit banknotes.
c-FACS offers improved efficiency for banknote authentication.
This chemometric approach enhances forensic capabilities in combating currency forgery.