Knowledge Commons of Institute of Automation,CAS
Using Scale Information to Improve SIFT-Based Electron Microscope Image Registration Method | |
Chen BH(陈波昊)1,3; Chang S(常胜)1,3; Chen X(陈曦)3; Han H(韩华)2,3,4,5 | |
2020-01 | |
会议名称 | Eleventh International Conference on Graphics and Image Processing (ICGIP 2019) |
卷号 | 11373 |
页码 | 113732C |
会议日期 | 2019-9 |
会议地点 | 中国浙江省杭州市 |
摘要 | Registration of electron microscopy (EM) images is one of the most important steps in reconstructing neurons. Image registration algorithm based on SIFT have been widely used in the EM image registration. But SIFT matching procedure both costs a lot of time and introduce massive false matches. In this paper, we propose an improved EM image registration method using the scale information of SIFT keypoints. In the feature matching procedure, our method saves up to 45.8% of the computation time compared to SIFT. We also added a preprocessing procedure for RANSAC to eliminate false matches in small-scale matches sets. Experimental results show that the method improves the accuracy of results on every test EM image set while highly reducing the registration time. |
关键词 | SIFT Image Registration RANSAC Electron Microscope |
收录类别 | EI |
资助项目 | Special Program of Beijing Municipal Science and Technology Commission[Z181100000118002] ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)[XDB32030200] ; Bureau of International Cooperation, Chinese Academy of Sciences[153D31KYSB20170059] |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48605 |
专题 | 脑图谱与类脑智能实验室_微观重建与智能分析 |
通讯作者 | Han H(韩华) |
作者单位 | 1.中国科学院大学 2.中国科学院大学未来技术学院 3.中国科学院自动化研究所 4.中国科学院脑科学与智能技术卓越创新中心 5.中国科学院自动化研究所模式识别国家实验室 |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Chen BH,Chang S,Chen X,et al. Using Scale Information to Improve SIFT-Based Electron Microscope Image Registration Method[C],2020:113732C. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Using_Scale_Informat(554KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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