期刊论文

A method to shape reconstruction from planar point sets with Gestalt proximity and simplification principle

Wu, Bo(wavelet778@sohu.com)

中文

测绘学报

1001-1595

2020

49

11

1485-1496

10.11947/j.AGCS.2020.20190406

The National Natural Science Foundation of China (No. 41961055); The Outstanding Youth Project of Education Department of Hunan Province (Nos. 19B078; 19C0272); The Hengyang Social Science Fund (No. 2018B (I) 002); The Open Fund Project of National-Local Joint Engineering Laboratory on Digital Preservation and Innovative Technologies for the Culture of Traditional Villages and Towns (No. CTCZ18K01); The National Key Research and Development Program of China (No. 2018YFE0207800).

本校为其他机构

针对经典Delaunay三角网平面点集形状重构方法存在的经验参数确定和容易出现不符合实际情况的碎洞问题,提出了一种顾及Gestalt邻近与简化原则的Delaunay三角网平面点集形状重构的算法SRGT。首先根据邻近性原则,采用双极差粗差探测技术来识别和定位Delaunay三角网中的极长边,逐步细化三角网中的内外边界;然后基于简化性原则,将形状重构的碎洞优化转化为粗差探测问题,并利用3σ粗差探测原则来实现碎洞的剔除。采用模拟与真实数据验证了本文算法的有效性。与4种经典算法(α-shape、χ-shape、边长比约束法以及∂RGG)进行对照试验,表明本文算法的优越性。模拟数据表明SRGT在面状点集为均匀或随机分布...

The widely used shape reconstruction algorithms based on Delaunay triangulation are far from sophisticated, and some problems are to be further addressed. First of all, the current methods involve a few of user-defined parameters, obstructing the effective use of them in practice. Secondly, the current methods cannot guarantee the perfect shape reconstruction if a planar point set follows a randomly distribution. To overcome these aforementioned problems, a method for planar point set shape reconstruction, namely SRGT (shape reconstruction base...