Download PDFOpen PDF in browserAnalysis of Kruskal's Algorithm for Segmenting ImageEasyChair Preprint no. 498711 pages•Date: February 8, 2021AbstractClustering / segmentation is widely used in the field of data mining. Pixel of the image is seen as a point and the edge is seen as the difference in intensity for two adjacent points. Then we determine the minimum spanning tree using Kruskal's algorithm. Edge that weight is greater than a threshold discarded, so that will be formed several sub tree. Threshold used to cut the minimum spanning tree generated by Kruskal's algorithm. Suppose S_{T1} = {T_{11}, T_{12}, ..., T_{1p}}, S_{T2} = {T_{21}, T_{22}, ..., T_{2q}}, respectively, is set of disjoint subtree of MST1, MST2 after the edge with the greater weight of the threshold is removed, and P(T_{ij}) is the set of points on sub tree T_{ij}, for i = 1, 2, dan j = 1, 2, ..., max{p,q}. Then p = q, and for each s Î {1, 2, ..., p}, there are t Î {1, 2, ..., p} such that P(T_{1s}) = P(T_{2t}). Keyphrases: minimum spanning tree, Segmentation, Sub Tree
