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All Journal Jurnal Informatika dan Teknik Elektro Terapan Jurnal Sisfokom (Sistem Informasi dan Komputer) JURNAL PETIK KOMPUTIKA - Jurnal Sistem Komputer KOMPUTA : Jurnal Ilmiah Komputer dan Informatika TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika Jurnal Sistem informasi dan informatika (SIMIKA) JISA (Jurnal Informatika dan Sains) E-Link: Jurnal Teknik Elektro dan Informatika JIKA (Jurnal Informatika) Abdimasku : Jurnal Pengabdian Masyarakat Indexia Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Riti, Yosefina Finsensia
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Health Professions Industrial & Manufacturing Engineering Social Sciences

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PERBANDINGAN ALGORITMA SOBEL, PREWITT, ROBERT, CANNY, KIRSCH, DAN LAPLACIAN OF GAUSSIAN DALAM DETEKSI TEPI PADA CITRA RONTGEN BATU SALURAN KEMIH Nugroho, Isaac Yeremia; Riti, Yosefina Finsensia; Wijaya, Ricky Junianto
TEKTRIKA Vol 9 No 2 (2024): TEKTRIKA Vol.9 No.2 2024
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/tektrika.v9i2.8059

Abstract

Urinary stones are a medical condition that occurs when the bladder cannot expel all the urine it contains, causing minerals in the urine to precipitate and harden. Several methods can be used to diagnose urinary stones, one of which in X-ray imaging. The results of X-ray images are usually blurry and have low contrast, making it difficult to read the edges of objects int the images. Therefore, edge detection in used, and in this study, six edge detection algorithms are employed to sharpen the edges of objects in an image, resulting in images with clear and sharp object edges. This study compares six edge detection algorithms: Sobel, Prewitt, Robert, Canny, Kirsch, and Laplacian of Gaussian on X-ray images of urinary stones. The research methodology involves collecting a dataset, preprocessing, converting images to grayscale, segmentation, and implementing the algorithms. The results of the edge detection algorithms are measured using MSE (Mean Squared Error) and PSNR (Peak Signal-to-Noise Ratio). The results show that the Canny algorithm has the highest average MSE of 3801.45 and the lowest average PSNR of 12.78, while the Sobel algorithm produces the worst results with the lowest average MSE of 3254.95 and the highest average PSNR of 13.72.Key Words: urinary stones, edge detection, grayscale, segmentation, MSE, PSNR
Co-Authors Agung, Mario Anugraha Ananda, Dionisius Reinaldo Anggelia, Dita Hargiani, Fransisca Xaveria Hendra Hendra Herijanto, Christopher Kevin Iskandar, Jonathan Steven Maximillian, Louis Mongkol, Nick Engelbert Nugroho, Isaac Yeremia Palis, Yohanes Junardi Putra, Yohanes Eka Saputro, Yulius Dani Eko Setiawan, Dionisius Reinaldo Ananda Siswanto, Paulus William Suwignyo, Angelicha Yuspitasari Tandjung, Stephanus Surijadarma Tanuwijaya, Padmavati Darma Tjahjadi, Jhonatan Laurensius Trisuwita, Nathanael Christian Perkasa Verado, Kyan Dillan Wijaya, Ricky Junianto