非重叠厚椭圆检测的尺度空间Radon变换

A. Goumeidane, D. Ziou, Nafaa Nacereddine
{"title":"非重叠厚椭圆检测的尺度空间Radon变换","authors":"A. Goumeidane, D. Ziou, Nafaa Nacereddine","doi":"10.1109/IPTA54936.2022.9784129","DOIUrl":null,"url":null,"abstract":"This paper presents a new elliptical structure detection method, combining the advantages of the multiscale Hessian, and the scale space Radon transform (SSRT) for an ellipse. The advantage of the former is twofold: highlighting the lines defining the ellipses present in the image and reducing the search space for these ellipses in the SSRT space, which will discard the false SSRT maxima. The subsequent application of the SSRT permits, in turn, to alleviate the computation load and to obtain, moreover, a good detection of thick ellipses when they are not threadlike. Experiments carried out on synthetic and real images have shown good detection of thick ellipses, with low computational overhead compared to the Elliptical Radon transform.","PeriodicalId":381729,"journal":{"name":"2022 Eleventh International Conference on Image Processing Theory, Tools and Applications (IPTA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Scale Space Radon Transform for Non Overlapping Thick Ellipses Detection\",\"authors\":\"A. Goumeidane, D. Ziou, Nafaa Nacereddine\",\"doi\":\"10.1109/IPTA54936.2022.9784129\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a new elliptical structure detection method, combining the advantages of the multiscale Hessian, and the scale space Radon transform (SSRT) for an ellipse. The advantage of the former is twofold: highlighting the lines defining the ellipses present in the image and reducing the search space for these ellipses in the SSRT space, which will discard the false SSRT maxima. The subsequent application of the SSRT permits, in turn, to alleviate the computation load and to obtain, moreover, a good detection of thick ellipses when they are not threadlike. Experiments carried out on synthetic and real images have shown good detection of thick ellipses, with low computational overhead compared to the Elliptical Radon transform.\",\"PeriodicalId\":381729,\"journal\":{\"name\":\"2022 Eleventh International Conference on Image Processing Theory, Tools and Applications (IPTA)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 Eleventh International Conference on Image Processing Theory, Tools and Applications (IPTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IPTA54936.2022.9784129\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Eleventh International Conference on Image Processing Theory, Tools and Applications (IPTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPTA54936.2022.9784129","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

结合椭圆的多尺度Hessian和尺度空间Radon变换(SSRT)的优点,提出了一种新的椭圆结构检测方法。前者的优点是双重的:突出显示定义图像中存在的椭圆的线条,并减少这些椭圆在SSRT空间中的搜索空间,这将丢弃假的SSRT最大值。SSRT的后续应用反过来又可以减轻计算负荷,并且可以很好地检测非线状的厚椭圆。在合成图像和真实图像上进行的实验表明,与椭圆Radon变换相比,该方法具有较好的厚椭圆检测效果,且计算量较低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Scale Space Radon Transform for Non Overlapping Thick Ellipses Detection
This paper presents a new elliptical structure detection method, combining the advantages of the multiscale Hessian, and the scale space Radon transform (SSRT) for an ellipse. The advantage of the former is twofold: highlighting the lines defining the ellipses present in the image and reducing the search space for these ellipses in the SSRT space, which will discard the false SSRT maxima. The subsequent application of the SSRT permits, in turn, to alleviate the computation load and to obtain, moreover, a good detection of thick ellipses when they are not threadlike. Experiments carried out on synthetic and real images have shown good detection of thick ellipses, with low computational overhead compared to the Elliptical Radon transform.
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
期刊最新文献
Special Session 3: Visual Computing in Digital Humanities Complex Texture Features Learned by Applying Randomized Neural Network on Graphs AAEGAN Optimization by Purposeful Noise Injection for the Generation of Bright-Field Brain Organoid Images Towards Fast and Accurate Intimate Contact Recognition through Video Analysis Draco-Based Selective Crypto-Compression Method of 3D objects
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1