Non-rigid point set registration for Chinese characters using structure-guided coherent point drift
点集注册
计算机科学
人工智能
点(几何)
计算机视觉
算法
点云
数学
迭代最近点
职位(财务)
作者
Hao Sun,Zhouhui Lian,Yingmin Tang,Jianguo Xiao
出处
期刊:International Conference on Image Processing日期:2014-10-01卷期号:: 4752-4756被引量:1
标识
DOI:10.1109/icip.2014.7025963
摘要
This paper proposes a non-rigid point set registration method called Structure-Guided Coherent Point Drift (SGCPD). The key idea of our method is to utilize structural information and combine the global and local point registrations together to improve the original Coherent Point Drift (CPD) algorithm. Specifically, given two point sets, we first align them using the CPD method with Localized Operator (CPDLO). Then we divide the target point set into several subsets and apply CPDLO to each subset. Finally, we implement the above two procedures until convergence. In this manner, more detailed information can be well exploited and thus higher registration accuracy can be achieved. Experimental results demonstrate that our method outperforms the original CPD approach on both point registration accuracy and skeleton decomposition accuracy for Chinese characters.