Deteksi Tepi Menggunakan Metode Operator Prewitt dan Kirsch pada Citra Uang Kertas
Year: 2025
Type: article
Abstract: The importance of edge detection in image processing, especially on banknote objects, prompted this research to carry out an analysis of two edge detection methods, namely the Prewitt and Kirsch operators. five images of banknotes with different denominations (2000, 5000, 10000, 20000 and 50000) were taken as research objects. The edge detection method is implemented using MATLAB, utilizing both Prewitt and Kirsch operators. Image quality assessment uses PSNR, Histogram and Pixel value parameters. The comparison results show that the Prewitt and Kirsch operators provide optimal edge detection results, producing clear and sharp edges in the banknote image. The edge detection quality assessment was carried out through the PSNR metric, and both showed PSNR values above 30 dB, indicating good quality in terms of clarity and accuracy. Comparison of the Histogram and Pixel values shows that the Kirsch method has a higher Histogram and the Prewitt method has a higher Pixel value.
Institution: Universitas Siber Muhammadiyah
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $19
OpenAlex ID: W4411361121