{"title":"通过构件树构建新颖的边缘检测框架","authors":"Zhijun Dai, Yihong Wu, Youji Feng","doi":"10.1109/ICMEW.2012.99","DOIUrl":null,"url":null,"abstract":"This paper proposes a new edge detection framework with component tree construction. This open framework is efficient for edge property computation and convenient for subsequent image processing. We detect edges according to the properties which are customized by framework rules. Experiments on using the framework for a new efficient implementation of Canny edge detector are reported. The results demonstrate that the tree construction is efficient and the framework is flexible.","PeriodicalId":385797,"journal":{"name":"2012 IEEE International Conference on Multimedia and Expo Workshops","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Edge Detection Framework by Component Tree Construction\",\"authors\":\"Zhijun Dai, Yihong Wu, Youji Feng\",\"doi\":\"10.1109/ICMEW.2012.99\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a new edge detection framework with component tree construction. This open framework is efficient for edge property computation and convenient for subsequent image processing. We detect edges according to the properties which are customized by framework rules. Experiments on using the framework for a new efficient implementation of Canny edge detector are reported. The results demonstrate that the tree construction is efficient and the framework is flexible.\",\"PeriodicalId\":385797,\"journal\":{\"name\":\"2012 IEEE International Conference on Multimedia and Expo Workshops\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE International Conference on Multimedia and Expo Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMEW.2012.99\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Multimedia and Expo Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMEW.2012.99","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Edge Detection Framework by Component Tree Construction
This paper proposes a new edge detection framework with component tree construction. This open framework is efficient for edge property computation and convenient for subsequent image processing. We detect edges according to the properties which are customized by framework rules. Experiments on using the framework for a new efficient implementation of Canny edge detector are reported. The results demonstrate that the tree construction is efficient and the framework is flexible.