摘要
针对曲线结构特征,引入极化角点指数作为特征角点的候选依据,提出了一种与曲线起始点位置无关的基于角点检测的多边形近似算法。实验证明,此方法快速有效,结果稳定,噪声抑制效果较好。
According to the structural characteristics of the curve, a new polygonal approximation algorithm based on corner detection is proposed by introducing a polarization cornerity index for the corner candidate. This algorithm has nothing to do with the position of the start point. A comprehensive analysis between the polygon approximation approaches and the corner detection approaches for the reconstruction of the curve is executed. The newly developed curve reconstruction algorithm was extensively tested on various shapes and is proved to be computationally fast and robust to noise. Experimental results are stable and closer to human visual effects.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2009年第12期1495-1498,共4页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金资助项目(40671159
40523055)
关键词
特征角点
角点检测
多边形近似
曲线重建
角点指数
极化角点指数
dominant point
corner detection
polygonal approximation
curve reconstruction
cornerity index
polarization cornerity index
作者简介
李乐林，博士生。现主要从事数字摄影测量、机载激光扫描数据三维重建、模式识别等方面的研究。E—mail：lilelindr@126．com
