{"title":"使用Roberst、Sobel、Prewitt和Canny方法实现数字成像比较","authors":"Kukuh Panggalih, Wawan Kurniawan, Windu Gata","doi":"10.29408/jit.v5i2.5923","DOIUrl":null,"url":null,"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.","PeriodicalId":13567,"journal":{"name":"Infotek : Jurnal Informatika dan Teknologi","volume":"34 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Implementasi Perbandingan Deteksi Tepi Pada Citra Digital Menggunakan Metode Roberst, Sobel, Prewitt dan Canny\",\"authors\":\"Kukuh Panggalih, Wawan Kurniawan, Windu Gata\",\"doi\":\"10.29408/jit.v5i2.5923\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":13567,\"journal\":{\"name\":\"Infotek : Jurnal Informatika dan Teknologi\",\"volume\":\"34 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Infotek : Jurnal Informatika dan Teknologi\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.29408/jit.v5i2.5923\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Infotek : Jurnal Informatika dan Teknologi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29408/jit.v5i2.5923","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
数字图像处理领域,如分割,已经成为一个广泛讨论的话题。分割的目的是将图像分割成多个部分或区域,使其不存在具有相似特征的重叠,如颜色、形状、纹理、强度等。分割过程一般分为三类分割,包括基于分类的分割(classification based segmentation)、基于边缘的分割(edge based segmentation)和基于区域的分割(region based segmentation)。边缘检测是一种系统的过程,用于检测数字图像中不固定或总是在直线或曲线中改变其亮度水平的像素。本研究的目的是比较使用图像对象的边缘检测方法。本研究采用Robert, Prewitt, Sobel和Canny的方法检测每张图像中的白色像素数。本研究使用的工具是Simulink Matlab,将对各算法的参数进行比较。然后从每种边缘检测方法中计算出白色像素的总数。
Implementasi Perbandingan Deteksi Tepi Pada Citra Digital Menggunakan Metode Roberst, Sobel, Prewitt dan Canny
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.