摘要
在反求工程中,基于散乱数据点的曲线重建研究有着重要的意义。本文给出了一种基于投影的移动最小二乘(MLS)曲线重建方法。首先快速搜索散乱点的K邻近,并引入相关性概念,应用MLS法细化散乱点集,最后通过排序和简化重建曲线。实验表明,细化点集准确地反映了数据点的形状和走向,拟合效果良好,效率较高。本文算法可应用于运动曲面重建中的轮廓线拟合。
The study of curve reconstruction based on unorganized data points has great importance in reverse engineering. We propose a curve reconstruction algorithm for planar unorganized point sets using the moving least squares （MLS） based on projection. First, we search fast for K-nearest neighbors; then, we introduce the concept of correlation for curve reconstruction of unorganized point cloud of varying thickness. After the unorganized point sets were thinned with the MLS, a smooth B-spline curve that faithfully represents their orientation and shape was reconstructed by ordering and parameterizing the thinned point sets. The curve reconstruction algorithm can be applied to profile curve fitting in kinematic surface reconstruction.
出处
《机械科学与技术》
CSCD
北大核心
2007年第4期455-458,共4页
Mechanical Science and Technology for Aerospace Engineering
基金
高等学校优秀青年教师教学科研奖励计划
江苏省创新人才培养基金项目(BK2001408)
航空科学基金项目(03H52059)资助
关键词
反求工程
散乱点集
移动最小二乘法
曲线重建
reverse engineering
unorganized point set
moving least-squares （MLS）
curve reconstruction
