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All Journal Jurnal Teknologi dan Sistem Komputer
Anton Yudhana
Department of Electrical Engineering, Faculty of Industrial Technology, Universitas Ahmad Dahlan. Jl. Ringroad Selatan, Kragilan, Tamanan, Kec. Banguntapan, Bantul, Daerah Istimewa Yogyakarta 55191| Universitas Ahmad Dahlan
Computer Science & IT Electrical & Electronics Engineering

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Edge Detection Analysis using Roberts, Sobel, Prewitt and Canny Methods Kgs Muhammad Rizky Alditra Utama; Rusydi Umar; Anton Yudhana
Jurnal Teknologi dan Sistem Komputer 2022: Publication In-Press
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2021.14209

Abstract

Border identification in a digital image is overgrowing in line with advances in computer technology for image processing. Edge detection becomes vital in recognizing the object of an image because the edge of the object in the image contains critical information, the information obtained can be either the size or shape of the object in the image so the edge quality must be good so that the information contained in it is not lost. This study uses edge detection with the Roberts, Sobel, Prewitt, and Canny method. The analysis shows that the calculation of PSNR on the Robetrs method has the highest value with an average of 44.19 dB, Sobel, Prewitt and Canny operators have PSNR values above 30 dB so that it is classified as a good image. The histogram value with the highest value is the Sobel operator with an average histogram value of 22.06, while the highest contrast value is the Canny operator has an average contrast value of 5.08. Based on testing, it can be concluded that the Roberts and Canny operators have the best image quality.
Co-Authors Kgs Muhammad Rizky Alditra Utama Rusydi Umar