Abstract

The field of digital image processing, such as segmentation, has become a widely discussed topic. Segmentation aims to divide the image into parts or regions so that there is no overlap with similar characteristics, such as color, shape, texture, and intensity. The segmentation process is generally divided into three groups of segmentation, including segmentation based on classification (classification based segmentation), segmentation based on edges (edge based segmentation), and segmentation based on region (region based segmentation). Edge detection is a systematic process used to detect pixels in digital images that are not fixed or always changing their brightness level in a line or curve. The purpose of this study is to compare edge detection methods using image objects. This research was conducted using the method of Robert, Prewitt, Sobel and Canny to detect the number of white pixels in each image. The tool used in this research is Simulink Matlab, where the parameters of each algorithm will be compared. Then the total number of white pixels is calculated from each edge detection method.

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