A novel dynamic minimum spanning tree based clustering method for image mining

DOI10.1080/09720529.2011.10698345zbMath1242.68241OpenAlexW2089121299MaRDI QIDQ2895977

S. John Peter

Publication date: 13 July 2012

Published in: Journal of Discrete Mathematical Sciences and Cryptography (Search for Journal in Brave)

Full work available at URL: http://www.connectjournals.com/file_html_pdf/1266705H_01_JDMSC_T25_14-5_pp405-419a.pdf

zbMATH Keywords

clusteringimage segmentationimage miningcluster separationweighted Euclidean minimum spanning tree

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Computing methodologies for image processing (68U10)

Cites Work

• Diameter partitioning
• Efficient algorithms for finding minimum spanning trees in undirected and directed graphs
• On the number of clusters
• A randomized linear-time algorithm to find minimum spanning trees
• Finding the Number of Clusters in a Dataset
• How Many Clusters? An Information-Theoretic Perspective
• Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters
• The NP-completeness column: An ongoing guide