Publication | Closed Access
Cluster analysis by binary morphology
94
Citations
15
References
1993
Year
Cluster ComputingEngineeringMachine LearningComputational AnalysisUnsupervised Machine LearningImage AnalysisMathematical MorphologyData ScienceData MiningPattern RecognitionUnsupervised LearningDocument ClusteringClustering (Nuclear Physics)Knowledge DiscoveryMorphologyMathematical Morphology OperationsStatistical Pattern RecognitionMultidimensional ObservationsUnsupervised Pattern ClassificationBinary MorphologyClassificationClustering (Data Mining)Fuzzy ClusteringPattern Recognition Application
An approach to unsupervised pattern classification that is based on the use of mathematical morphology operations is developed. The way a set of multidimensional observations can be represented as a mathematical discrete binary set is shown. Clusters are then detected as well separated subsets by means of binary morphological transformations.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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