Geometric and Grayscale Template Matching for Saudi Arabian Riyal Paper Currency Recognition

Abstract

<p>Detecting the authenticity of paper currencies using automated based Paper Currency Recognition (PCR) with image processing techniques was still a hot topic of discussion, due to the circulation of counterfeit currency that was still overwhelming in some countries. There was a downside along with this advancement in technology in the field of color printing, duplication, and scanning, because it was became one of the supporting factors of the increasing crime rate in production of counterfeit money. Our system has performed a PCR approach based on image processing techniques. In this study, the SAR banknote was the object to be recognized and detected its authenticity with the development of the previous method, which was incorporating the Geometric Template Matching and Grayscale Template Matching. In addition to the pattern recognition process, the classification process on 1 SAR, 2 SAR, 5 SAR, and 10 SAR was also performed. From PCR test up to 100 sample data, for each tested banknote value obtained the average value of the best accuracy level from incorporating GeoMatchingScore and GrayMatchingScore for the classification process was 95.25%. While the average level of system accuracy in recognizing counterfeit money on each banknote obtained a maximum value of 100%.</p>

AlFloos: a balanced dataset for the sixth issue of the Saudi Arabian currency banknote*

“…The author in [13] scanned 110 banknotes representing 8 denominations of the fourth issue of the Saudi Arabian currency. The authors in [14] demonstrated a paper currency recognition and classification for the old fifth issue of the Saudi Arabian banknote by collecting 100 samples of the following denominations: 1, 5, 10, and 50 Saudi Arabian Riyals. The authors in [15] presented a banknote recognition software for various currencies, including the Saudi Arabian currency.…”