一种基于密度的面向线段的聚类算法

Line oriented clustering algorithm based on density

分析了密度聚类算法(DBSCAN)的局限性,在此基础上提出了一种基于密度的面向线段的聚类方法,将DBSCAN中聚类的对象由点转变为线段。在对点聚类的基础上,研究了线段聚类的特点。该算法可以有效处理分布不均匀的线段对象集,发现分布密度不同的各种簇。通过试验证明了该方法的可行性与有效性。

After analyzing the deficiencies of the traditional clustering algorithm DBSCAN （Density Based Spatial Clustering of Applications with Noise）, a line oriented clustering method based on DBSCAN was proposed. The object clustered changed from the point to the line. The characteristics of line oriented clustering method were studied based on the point oriented clustering method. The algorithm can deal with irregular line sets and find out clusters with different densities. It is proved to be workable and validated by a test.