Using Scale Information to Improve SIFT-Based Electron Microscope Image Registration Method
文献类型:会议论文
作者 | Chen BH(陈波昊)3,5![]() ![]() ![]() ![]() |
出版日期 | 2020-01 |
会议日期 | 2019-9 |
会议地点 | 中国浙江省杭州市 |
关键词 | SIFT Image Registration RANSAC Electron Microscope |
卷号 | 11373 |
页码 | 113732C |
英文摘要 | 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. |
语种 | 英语 |
源URL | [http://ir.ia.ac.cn/handle/173211/48605] ![]() |
专题 | 类脑智能研究中心_微观重建与智能分析 |
通讯作者 | Han H(韩华) |
作者单位 | 1.中国科学院脑科学与智能技术卓越创新中心 2.中国科学院大学未来技术学院 3.中国科学院大学 4.中国科学院自动化研究所模式识别国家实验室 5.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]. 见:. 中国浙江省杭州市. 2019-9. |
入库方式: OAI收割
来源:自动化研究所
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