使用哈里斯角响应测量的显微图像自动对焦。

Madhu S Sigdel, Madhav Sigdel, Semih Dinç, İmren Dinç, Marc L Pusey, Ramazan S Aygün
{"title":"使用哈里斯角响应测量的显微图像自动对焦。","authors":"Madhu S Sigdel,&nbsp;Madhav Sigdel,&nbsp;Semih Dinç,&nbsp;İmren Dinç,&nbsp;Marc L Pusey,&nbsp;Ramazan S Aygün","doi":"10.1109/SECON.2014.6950754","DOIUrl":null,"url":null,"abstract":"<p><p>One of the difficulties for proper imaging in microscopic image analysis is defocusing. Microscopic images such as cellular images, protein images, etc. need properly focused image for image analysis. A small difference in focal depth affects the details of an object significantly. In this paper, we introduce a novel auto-focusing approach based on Harris Corner Response Measure (HCRM) and compare the performance with some existing auto-focusing methods. We perform our experiments on protein images as well as a simulated image stack to evaluate the performance of our method. Our results show that our HCRM-based technique outperforms other techniques.</p>","PeriodicalId":90950,"journal":{"name":"Proceedings of IEEE Southeastcon. IEEE Southeastcon","volume":"2014 ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2014-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/SECON.2014.6950754","citationCount":"2","resultStr":"{\"title\":\"Autofocusing for Microscopic Images using Harris Corner Response Measure.\",\"authors\":\"Madhu S Sigdel,&nbsp;Madhav Sigdel,&nbsp;Semih Dinç,&nbsp;İmren Dinç,&nbsp;Marc L Pusey,&nbsp;Ramazan S Aygün\",\"doi\":\"10.1109/SECON.2014.6950754\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>One of the difficulties for proper imaging in microscopic image analysis is defocusing. Microscopic images such as cellular images, protein images, etc. need properly focused image for image analysis. A small difference in focal depth affects the details of an object significantly. In this paper, we introduce a novel auto-focusing approach based on Harris Corner Response Measure (HCRM) and compare the performance with some existing auto-focusing methods. We perform our experiments on protein images as well as a simulated image stack to evaluate the performance of our method. Our results show that our HCRM-based technique outperforms other techniques.</p>\",\"PeriodicalId\":90950,\"journal\":{\"name\":\"Proceedings of IEEE Southeastcon. IEEE Southeastcon\",\"volume\":\"2014 \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1109/SECON.2014.6950754\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of IEEE Southeastcon. IEEE Southeastcon\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SECON.2014.6950754\",\"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 IEEE Southeastcon. IEEE Southeastcon","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SECON.2014.6950754","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

在显微图像分析中,正确成像的难点之一是离焦。显微图像,如细胞图像,蛋白质图像等,需要适当聚焦的图像进行图像分析。焦深的微小差异会显著影响物体的细节。本文提出了一种基于哈里斯角响应测度(Harris Corner Response Measure, HCRM)的自动对焦方法,并与现有的自动对焦方法进行了性能比较。我们在蛋白质图像和模拟图像堆栈上进行实验来评估我们的方法的性能。我们的结果表明,我们基于hcrm的技术优于其他技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Autofocusing for Microscopic Images using Harris Corner Response Measure.

Autofocusing for Microscopic Images using Harris Corner Response Measure.

Autofocusing for Microscopic Images using Harris Corner Response Measure.

Autofocusing for Microscopic Images using Harris Corner Response Measure.

One of the difficulties for proper imaging in microscopic image analysis is defocusing. Microscopic images such as cellular images, protein images, etc. need properly focused image for image analysis. A small difference in focal depth affects the details of an object significantly. In this paper, we introduce a novel auto-focusing approach based on Harris Corner Response Measure (HCRM) and compare the performance with some existing auto-focusing methods. We perform our experiments on protein images as well as a simulated image stack to evaluate the performance of our method. Our results show that our HCRM-based technique outperforms other techniques.

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