Abstract
An important digital image processing is image segmentation, which separates objects from the background for further analysis. One segmentation technique is edge detection, which looks for boundaries between areas of different brightness. This article compares four edge detection methods: Roberts, Prewitt, Sobel, and Canny. The results show that, despite requiring more complex computations, Canny's method produces the sharpest and best connected edges; Sobel and Prewitt's method, on the other hand, is faster and simpler than Roberts' method, but is less effective in dealing with noise and often produces edges that are not connected to the plane. The choice of edge detection method depends on the application. Sobel and Prewitt are good for speed and stability, and Roberts is suitable for fast processing of images with minimal noise.
Published Version
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