Detecting the Authenticity of 2022 Emission Banknotes Based on Watermark with the Canny Edge Detection Method

Authors

  • Dimas Arya Universitas Islam Negeri Sumatera Utara
  • M. Arif Aulia Universitas Islam Negeri Sumatera Utara
  • Reza Althoriq Universitas Islam Negeri Sumatera Utara

Keywords:

authenticity detection, paper money, canny edge detection

Abstract

Money is a legal means of payment circulated by the government in a country, either in the form of banknotes, gold, silver or other valuable metals which are designed and printed with certain shapes and images. Detecting is a way of checking something using certain techniques. With advances in information technology and easy access to information, many criminals misuse it. Image processing is increasingly developing its function in systems for recognizing unique objects, such as watermarks on rupiah banknotes. In image segmentation there are also several methods, for example canny edge detection. Canny edge detection is a method that produces a different image appearance by displaying a relief effect in it. The aim of this research is to detect the authenticity of watermarked banknotes using the canny edge detection method. The process of using the method above includes image acquisition, gray scale operations, morphological operations, then smart edge detection. There are 8 images used in this research consisting of nominal banknotes of 1,000, 2,000, 5,000, 10,000, 20,000, 50,000, 75,000 and 100,000. The final result of the canny edge detection process is a collection of pixels that are used to determine whether an image has a watermark or not. From this research, the accuracy of the watermark detection program on banknotes using the canny edge detection method to detect the authenticity of money was 75%.

References

U. Rekomendasi Kebijakan Bidang Kesehatan, B. Setiaji, P. Kodrat Pramudho, P. R. Kebijakan Upaya Kesehatan BKPK Kemkes, and P. Studi Magister, “PEMANFAATAN TEKNOLOGI INFORMASI BERBASIS DATA DAN JURNAL,” Jurnal Inovasi Riset Ilmu Kesehatan, vol. 1, no. 3, 2022.

B. B. Wahono, “PERANCANGAN TATAKELOLA TEKNOLOGI INFORMASI UNTUK PENINGKATAN LAYANAN SISTEM INFORMASI KESEHATAN (STUDI KASUS DINAS KESEHATAN KABUPATEN JEPARA),” Jurnal SIMETRIS, vol. 6, 2015.

G. Lisanawati, “Cyber Child Sexual Exploitation dalam Perspektif Perlindungan atas Kejahatan Siber,” vol. 8, 2013, [Online]. Available: http://journal.unnes.ac.id/nju/index.php/pandecta

I. Novia Putri, “IMPLEMENTASI MIKROKONTROLER DAN SINAR ULTRAVIOLET PADA ALAT PENDETEKSI UANG PALSU,” vol. 8, no. 1, 2022, [Online]. Available: http://ejournal.fikom-unasman.ac.id

L. Mann and S. Roche, “Recent Trends in Banknote Counterfeiting.”

C. A. Madundang, “PENGATURAN HUKUM MENGENAI PEMALSUAN UANG RUPIAH MENURUT PASAL 244 SAMPAI DENGAN PASAL 252 KUHP,” Lex Privatum, vol. 4, no. 4, pp. 5–13, Apr. 2016.

E. Maximiliaan Tentua, K. Kunci, A. Tindak Pidana, and K. Internasional, “ALASAN-ALASAN SUATU TINDAK PIDANA DAPAT MASUK KATAGORI KEJAHATAN INTERNASIONAL.”

Zulkarnaen, “Pemalsuan Uang dan Stabilitas Kamdagri,” Jurnal Ilmu Kepolisian, vol. 14, no. 3, pp. 210–218, Dec. 2020.

M. Ball, “Recent Trends in Banknote Counterfeiting.”

Z. Lubis, S. Annisa, and A. Najmita, “Perancangan Aplikasi Jaringan Syaraf Tiruan (Neural Networks) Untuk Pedeteksi Keaslian Uang Kertas,” 2020.

M. H. Alshayeji, M. Al-Rousan, and D. T. Hassoun, “Detection method for counterfeit currency based on bit-plane slicing technique,” International Journal of Multimedia and Ubiquitous Engineering, vol. 10, no. 11, pp. 225–242, 2015, doi: 10.14257/ijmue.2015.10.11.22.

Y. Ramadhan Nasution, “ALAT PENGENAL NOMINAL UANG UNTUK TUNANETRA MENGGUNAKAN SENSOR WARNA DAN ULTRAVIOLET,” JISTech, vol. 4, no. 1, 2019.

D. Sathik and Nr. Shabnam Parveen, “FEATURE EXTRACTION ON COLORED X-RAY IMAGES BY BIT-PLANE SLICING TECHNIQUE,” 2010.

A. Rahayu, “Analisa dan Implementasi Metode Zhang-Suen Dalam Pengerangkaan (Skeleton) Pada Citra Untuk Mengurangi Redundant,” JURIKOM (Jurnal Riset Komputer), vol. 7, no. 1, p. 156, Feb. 2020, doi: 10.30865/jurikom.v7i1.1946.

W. Supriyatin, “Perbandingan Metode Sobel, Prewitt, Robert dan Canny pada Deteksi Tepi Objek Bergerak,” ILKOM Jurnal Ilmiah, vol. 12, no. 2, pp. 112–120, Aug. 2020, doi: 10.33096/ilkom.v12i2.541.112-120.

A. Salam, H. Sunandar, and I. Saputra, “ANALISA DETEKSI TEPI CITRA MENGGUNAKAN METODE KRISCH DAN UNSHARP MASKING PADA IMAGE CT SCAN,” 2018.

Sukatmi, “KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer,” KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer , vol. 1, no. 1, pp. 1–4, Feb. 2017.

I. Ummah and N. Yannuansa, “ANALISIS PENDETEKSIAN TEPI OBJEK PADA PENGOLAHAN CITRA,” Seminar Nasional SAINSTEKNOPAK Ke, vol. 4, pp. 118–122, 2020.

R. Rokhana et al., “Convolutional Neural Network untuk Pendeteksian Patah Tulang Femur pada Citra Ultrasonik B-Mode,” 2019.

T. Bariyah and M. Arif Rasyidi, “Convolutional Neural Network Untuk Metode Klasifikasi Multi-Label Pada Motif Batik Convolutional Neural Network for Multi-Label Batik Pattern Classification Method.”

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Published

2023-07-31

How to Cite

Arya, D., Aulia, M. A. ., & Althoriq, R. . (2023). Detecting the Authenticity of 2022 Emission Banknotes Based on Watermark with the Canny Edge Detection Method. Bigint Computing Journal, 1(2), 53–61. Retrieved from https://journal.aira.or.id/index.php/bigint/article/view/778

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