{"title":"仅使用方向信息的有效视网膜血管检测","authors":"Maria Frucci, D. Riccio, G. S. D. Baja, L. Serino","doi":"10.1109/SITIS.2015.38","DOIUrl":null,"url":null,"abstract":"We present an effective unsupervised segmentation method that is based only on the use of the direction map built in correspondence of the retinal image by assigning each pixel one out of twelve discrete directions. The segmentation method works on the green channel of RGB retina images and does not require any pre-processing phase. The method has been checked on the DRIVE dataset producing satisfactory results both qualitatively and quantitatively.","PeriodicalId":128616,"journal":{"name":"2015 11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Effective Retinal Blood Vessel Detection Using Only Directional Information\",\"authors\":\"Maria Frucci, D. Riccio, G. S. D. Baja, L. Serino\",\"doi\":\"10.1109/SITIS.2015.38\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present an effective unsupervised segmentation method that is based only on the use of the direction map built in correspondence of the retinal image by assigning each pixel one out of twelve discrete directions. The segmentation method works on the green channel of RGB retina images and does not require any pre-processing phase. The method has been checked on the DRIVE dataset producing satisfactory results both qualitatively and quantitatively.\",\"PeriodicalId\":128616,\"journal\":{\"name\":\"2015 11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SITIS.2015.38\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SITIS.2015.38","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Effective Retinal Blood Vessel Detection Using Only Directional Information
We present an effective unsupervised segmentation method that is based only on the use of the direction map built in correspondence of the retinal image by assigning each pixel one out of twelve discrete directions. The segmentation method works on the green channel of RGB retina images and does not require any pre-processing phase. The method has been checked on the DRIVE dataset producing satisfactory results both qualitatively and quantitatively.