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浏览/检索结果: 共6条，第1-6条 帮助 已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择发表日期升序发表日期降序作者升序作者降序提交时间升序提交时间降序题名升序题名降序 Precise iterative closest point algorithm with corner point constraint for isotropic scaling registration 期刊论文 Multimedia Systems, 2017, 页码: 1-8 作者:  Du, Shaoyi;  Cui, Wenting;  Wu, Liyang;  Zhang, Sirui;  Zhang, Xuetao 收藏  |  浏览/下载：5/0  |  提交时间：2019/11/26 Closed form solutions  Corner point  Isotropic scaling registrations  Iterative closest point algorithm  Iterative Closest Points  Objective functions  Registration precision  Scaling transformation   A survey of iterative closest point algorithm 期刊论文 Proceedings - 2017 Chinese Automation Congress, CAC 2017, 2017, 卷号: 2017-January, 页码: 4395-4399 作者:  Wang, Fang;  Zhao, Zijian 收藏  |  浏览/下载：9/0  |  提交时间：2019/12/12 3D point set  convergence speed  ICP algorithm  registration  registration precision   A Survey of Iterative Closest Point Algorithm 会议论文 Chinese Automation Congress (CAC), OCT 20-22, 2017 作者:  Wang, Fang;  Zhao, Zijian 收藏  |  浏览/下载：4/0  |  提交时间：2019/12/31 registration  3D point set  ICP algorithm  registration precision  convergence speed   Application of bonebed-malleus short process registration in minimally invasive cochlear implantation 期刊论文 Computer Assisted Surgery, 2016, 卷号: 21, 页码: 30-36 作者:  Ke, Jia;  Zhang, Shaoxing;  Li, Changsheng;  Zhu, Yunfeng;  Hu, Lei 收藏  |  浏览/下载：5/0  |  提交时间：2019/12/30 Cochlear implant  minimally invasive surgical procedures  navigation  precision  registration   几种经典相似性度量的比较研究 期刊论文 2010, 2010 刘宝生; 闫莉萍; 周东华; LIU Bao-sheng; YAN Li-ping; ZHOU Dong-hua 收藏  |  浏览/下载：1/0 The registration of aerial infrared and visible images (EI CONFERENCE) 会议论文 2010 International Conference on Educational and Information Technology, ICEIT 2010, September 17, 2010 - September 19, 2010, Chongqing, China Sun M.; Bao Z.; Liu J.; Wang Y.; Quan Y. 收藏  |  浏览/下载：16/0  |  提交时间：2013/03/25 In order to solve the registration problem of different source image existed on aerial image fusion  algorithms based on Particle Swarm Optimization (PSO) are applied as search strategy in this paper  and Alignment Metric (AM) is used as judgment. This study has realized the different source image registration of infrared and visible light with high speed  high accuracy and high reliability. Basically  with little restriction of gray level properties  a new alignment measure is applied  which can efficiently measure the image registration extent and tolerate noise well. Even more  the intelligent optimization algorithm - Particle Swarm Optimization (PSO) is combined to improve the registration precision and rate of infrared and visible light. Experimental results indicate that  the study attains the registration accuracy of pixel level  and every registration time is cut down over 40 percent compared to traditional method. The match algorithm based on AM  solves the registration problem that greater differences between different source images are existed on gray and characteristic. At the same time  the adoption of combining the intelligent optimization algorithms significantly improves the searching efficiency and convergence speed of the algorithms  and the registration result has higher accuracy and stability  which builds up solid foundation for different source image fusion. The method in this paper has a magnificent effect  and is easy for application and very suitable for engineering use. 2010 IEEE.