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长春光学精密机械与物... [1]
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会议论文 [2]
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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
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  |  
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
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  |  
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
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  |  
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
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  |  
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
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  |  
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.
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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.
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