首页|非刚体图像配准中点对应关系的模糊分配技术

非刚体图像配准中点对应关系的模糊分配技术

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非刚体图像配准中经常会用到基于特征的配准法,其中以基于点特征的联合估计法最为常用.为了解决传统的基于迭代最近点的联合估计法易陷入局部最小值点的问题,提出了模糊分配技术.利用点对之间的距离产生对应矩阵,此矩阵的取值随点集之间相对位置的变化连续改变,代替传统算法中对应矩阵的0-1取值模式.这样可以避免过早地排除掉潜在的对应点,从而可以最大概率地收敛于全局最优点,同时在迭代配准过程中逐步减小距离控制系数,以实现由粗到细的配准过程.仿真实验表明,和形状上下文、中心预对齐及传统方法相比,此方法可以使配准误差分别减小到77.5%、32.6%和23.2%左右.
Fuzzy Assignment of Point Correspondence in Non-rigid Image Registration
Feature-based registration methods are often used in non-rigid image registration,among which joint estimation method based on point features is the most commonly used.The traditional joint estimation method based on the iterative closest point is easy to fall into the local optimum.To address this problem,in this paper,a fuzzy assignment algorithm is proposed,with which the distance between point pairs is used to generate the corre-sponding matrix,and the value of this matrix changes continuously with the change of the relative positions between point sets,replacing the 0-1 value pattern of the corresponding matrix in the traditional algorithm.In this way,the potential corresponding points can avoid being eliminated prematurely,and the convergence to the global opti-mum can be achieved with maximum probability.At the same time,the distance control coefficient is gradually re-duced in the iterative registration process to make the registration process from being coarse to fine.The simulation results show that,compared with shape context,center prealignment and traditional methods,the registration errors of this method can be reduced to 77.5%,32.6%and 23.2%respectively.

non-rigid image registrationiterative closest pointjoint estimationfuzzy assignmentglobal optimumpoint correspondece

上官晋太、刘丽丽

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长治学院计算机系,山西 长治 046011

非刚体图像配准 迭代最近点 联合估计 模糊分配 全局最优 点对应关系

2024

长治学院学报
长治学院

长治学院学报

影响因子:0.116
ISSN:1673-2014
年,卷(期):2024.41(5)