基于分数阶微分的岩石裂隙提取

Weixing Wang, Juan Wan, Zhao Yang
{"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}
引用次数: 2

摘要

提出了一种基于分数阶微分理论的岩石裂隙图像分割算法。通过对新的覆盖模板进行迭代卷积,可以比在图像处理中应用的天思模块更有效地提取岩石裂缝图像上的高频信号。本研究对于拓展分数阶微分的应用领域,进行有意义的探索具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信