{"title":"用定向连接法自动检测太阳环","authors":"Jong Kwan Lee, Timothy S Newman, G. A. Gary","doi":"10.1109/ICPR.2004.1333766","DOIUrl":null,"url":null,"abstract":"An automated technique to segment solar coronal loops from intensity images of the sun's corona is introduced. It exploits physical characteristics of the solar magnetic field to enable robust extraction from noisy images. The technique is a constructive curve detection approach, constrained by collections of estimates of the magnetic field's orientation. Its effectiveness is evaluated through experiments on synthetic and real coronal images.","PeriodicalId":335842,"journal":{"name":"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Automated detection of solar loops by the oriented connectivity method\",\"authors\":\"Jong Kwan Lee, Timothy S Newman, G. A. Gary\",\"doi\":\"10.1109/ICPR.2004.1333766\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An automated technique to segment solar coronal loops from intensity images of the sun's corona is introduced. It exploits physical characteristics of the solar magnetic field to enable robust extraction from noisy images. The technique is a constructive curve detection approach, constrained by collections of estimates of the magnetic field's orientation. Its effectiveness is evaluated through experiments on synthetic and real coronal images.\",\"PeriodicalId\":335842,\"journal\":{\"name\":\"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.2004.1333766\",\"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 of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2004.1333766","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automated detection of solar loops by the oriented connectivity method
An automated technique to segment solar coronal loops from intensity images of the sun's corona is introduced. It exploits physical characteristics of the solar magnetic field to enable robust extraction from noisy images. The technique is a constructive curve detection approach, constrained by collections of estimates of the magnetic field's orientation. Its effectiveness is evaluated through experiments on synthetic and real coronal images.