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Cluster analysis by binary morphology

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3 Author(s)
Postaire, J.-G. ; Centre d''Automatique, Univ. des Sci. et Tech. de Lille Flandres Artois, Villeneuve d''Ascq, France ; Zhang, R.D. ; Lecocq-Botte, C.

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

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Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:15 ,  Issue: 2 )