Line oriented clustering algorithm based on density
一种基于密度的面向线段的聚类算法

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.