{"title":"一种基于支持向量分类的边缘检测新方法","authors":"Jing Lei, Xue-qin Shen","doi":"10.1109/ICMLC.2002.1175339","DOIUrl":null,"url":null,"abstract":"An edge detection method based on a support vector machine is introduced. We use support vector classification (SVC) to detect image edges. With support vector classification, we can observe that: (1) it is very convenient for gray level images whose background and foreground lightness have large differences; (2) we can compress the images through the so-called support vector.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"41 22","pages":"1762-1764 vol.4"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/ICMLC.2002.1175339","citationCount":"2","resultStr":"{\"title\":\"A new method for edge detection based on support vector classification\",\"authors\":\"Jing Lei, Xue-qin Shen\",\"doi\":\"10.1109/ICMLC.2002.1175339\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An edge detection method based on a support vector machine is introduced. We use support vector classification (SVC) to detect image edges. With support vector classification, we can observe that: (1) it is very convenient for gray level images whose background and foreground lightness have large differences; (2) we can compress the images through the so-called support vector.\",\"PeriodicalId\":90702,\"journal\":{\"name\":\"Proceedings. International Conference on Machine Learning and Cybernetics\",\"volume\":\"41 22\",\"pages\":\"1762-1764 vol.4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/ICMLC.2002.1175339\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. International Conference on Machine Learning and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMLC.2002.1175339\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. International Conference on Machine Learning and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2002.1175339","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new method for edge detection based on support vector classification
An edge detection method based on a support vector machine is introduced. We use support vector classification (SVC) to detect image edges. With support vector classification, we can observe that: (1) it is very convenient for gray level images whose background and foreground lightness have large differences; (2) we can compress the images through the so-called support vector.
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