{"title":"基于分数阶微分的岩石裂隙提取","authors":"Weixing Wang, Juan Wan, Zhao Yang","doi":"10.1109/IWISA.2010.5473312","DOIUrl":null,"url":null,"abstract":"This paper proposes a rock fracture image segmentation algorithm based on fractional differential theory. By iteratively convoluted with the new covering templates, the high frequency signals on a rock fracture image can be more effectively extracted than the Tiansi module which has been applied in image processing applications. This study is very meaningful for expanding the application areas of fractional differential and carrying out a significant exploration.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Rock Fracture Extracting on Fractional Differential\",\"authors\":\"Weixing Wang, Juan Wan, Zhao Yang\",\"doi\":\"10.1109/IWISA.2010.5473312\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a rock fracture image segmentation algorithm based on fractional differential theory. By iteratively convoluted with the new covering templates, the high frequency signals on a rock fracture image can be more effectively extracted than the Tiansi module which has been applied in image processing applications. This study is very meaningful for expanding the application areas of fractional differential and carrying out a significant exploration.\",\"PeriodicalId\":298764,\"journal\":{\"name\":\"2010 2nd International Workshop on Intelligent Systems and Applications\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 2nd International Workshop on Intelligent Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWISA.2010.5473312\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 2nd International Workshop on Intelligent Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWISA.2010.5473312","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Rock Fracture Extracting on Fractional Differential
This paper proposes a rock fracture image segmentation algorithm based on fractional differential theory. By iteratively convoluted with the new covering templates, the high frequency signals on a rock fracture image can be more effectively extracted than the Tiansi module which has been applied in image processing applications. This study is very meaningful for expanding the application areas of fractional differential and carrying out a significant exploration.