M. Khairudin, R. Mahaputra, M. Luthfi Hakim, Asri Widowati, B. Rahmatullah, A.A.M. Faudzi
Choosing a quality image is the goal of image processing of two-dimensional (2D) images through computer vision. Image processing consists of stages, namely acquisition, pre-processing (enhancement), segmentation, representation and description, as well as introduction and interpretation. Edge detection is a stage in image processing that aims to find the pattern of an image. This study analyzes the quality of 2D images through edge detection techniques with a comparison of various techniques and error analysis. The comparison of edge detection in this study was performed on images produced using some techniques, such as Canny, Sobel, Prewitt, and Roberts. To analyze the error, Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) were used. This study was conducted using Matlab by comparing six different images of lung, car, leaf, apple, cat, and motorcycle. The results show that using edge detection with the Canny technique may result in the best MSE and PSNR values. Consistent results of six images detected also show that Canny technique produced the best MSE and PSNR values among the results produced by the Sobel, Prewitt, and Roberts techniques. © (2023), (International Association of Engineers). All Rights Reserved.
Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Yogyakarta, Yogyakarta, Karangmalang, 55281, Indonesia; Mechatronics Engineering, Faculty of Engineering, Universitas Negeri Yogyakarta, Yogyakarta, Karangmalang, 55281, Indonesia; Department of Mechatronics Engineering, Faculty of Engineering, Universitas Negeri Yogyakarta, Yogyakarta, Karangmalang, 55281, Indonesia; Department of science education, Faculty of Mathematics and Natural Sciences, Universitas Negeri Yogyakarta, Yogyakarta, Karangmalang, 55281, Indonesia; Faculty of Art, Computing, and Creative Industry, Universiti Pendidikan Sultan Idris (UPSI), Perak, Tanjung Malim, Malaysia; School of Electrical Engineering, Universiti Teknologi Malaysia, Johor, Malaysia
