基于Alpha-Shape的多尺度曲线分解

Zhuangzhi Wu, Lu Feng
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引用次数: 1

摘要

在地图学中,曲线简化是一个反复出现的问题。这样做的目的是在强调曲线的主要特征的同时,去掉不相关的细节。曲线分解是曲线化简的预处理。目前的技术大多属于空间领域(最小二乘法、活动轮廓、点选择)。然而,一些应用于频域的技术(傅里叶变换,小波)也被引入。本文提出了一种新的基于alpha形状的曲线分解频率方法。首先利用alpha形状提取曲线包络线;然后,通过过滤后的中轴变换(FMAT)生成基础层。通过使用不同的alpha值,我们可以得到不同尺度的基础层。最后提出了今后的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-scale Curve Decomposition Based on Alpha-Shape
In cartography curve simplification is a recurrent problem. The purpose is to remove irrelevant details while emphasizing the main features of the curve. Decomposition of curve is preprocessing of curve simplification. Most of the current techniques belong to the spatial domain (least square method, active contour, point selection). However, some techniques applying to the frequency domain (Fourier transform, wavelets) have also been introduced. This paper presents a new frequency method for curve decomposition based on alpha shape. It firstly utilizes the alpha shape to extract the envelope of the curve. And then, the filtered medial axis transform (FMAT) generate the base layer. By using different alpha values, we can get base layer in different scales. Future directions for work are presented at the end of this paper.
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