Cluster dynamics studied with the phase-space minimum spanning tree approach

Cluster Validity with Minimum Spanning Tree Based Clustering

Clustering is a process of discovering groups of objects such that the objects of the same group are similar, and objects belonging to different groups are dissimilar. A number of clustering algorithms exist that can solve the problem of clustering, but most of them are very sensitive to their input parameters. Therefore it is very important to evaluate the result of them. The minimum spanning ...

A Novel Algorithm for Central Cluster Using Minimum Spanning Tree

The minimum spanning tree clustering algorithm is capable of detecting clusters with irregular boundaries. In this paper we propose a novel minimum spanning tree based clustering algorithm. The algorithm produces k clusters with center and guaranteed intra-cluster similarity. The algorithm uses divisive approach to produce k number of clusters. The center points are considered as representative...

4 Minimum Spanning Tree

This first algorithm is quite simple. (Though this was probably known earlier, its proof can be found in Prof. Indyk’s 1999 paper “Sublinear Time Algorithms for Metric Space Problems”.) Let Dij denote the distance between a pair of points i and j, over m total points. The entries of Dij must satisfy the triangle inequality; additionally the matrix is symmetric. Note that the matrix size (i.e., ...

Image Registration with Minimum Spanning Tree Algorithm

Registration is a fundamental task in image processing and quite a few registration techniques have been developed in various fields. In this paper we propose a novel graphrepresentation method for image registration with Rényi entropy as the dissimilarity metric between images. The image matching is performed by minimizing the length of the minimum spanning tree (MST) which spans the graph gen...

Minimum spanning tree with hop restri