摘要
针对传统的基于距离计算相似性聚类方法的局限性,提出一种基于几何形状的点集聚类方法。该方法可以从离散的点集中提取出具有某种拓扑几何形状特征的目标对象。实验证明,该方法可以有效地检测分布呈小饶度的曲线形状的点集,在一定程度上克服了基于距离检测方法的局限性,可以在工程图纸识别、计算机视觉、遥感识别等领域得到应用。
Aimed at the limitations of clustering of the traditional calculation of similarity based on distance, a method of point-set clustering based on topology geometry-figure is proposed. Some kinds of objects with the geometric characteristics wishing to be needed are extracted from the discrete point-sets. The experiment shows that the method can detect effectively the curve points of small curvature, to some extent, it overcomes the limitation of the method based distance. It can be applied in the areas of engineering drawings recognition, computer vision, remote sensing recognition and so on.
出处
《计算机工程与设计》
CSCD
北大核心
2008年第10期2613-2615,共3页
Computer Engineering and Design
关键词
聚类
几何形状
离散
饶度
曲线提取
clustering
geometry-figure
discrete
curvature
curve-extracting
