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Issue No.02 - February (1993 vol.15)
pp: 170-180
ABSTRACT
<p>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.</p>
INDEX TERMS
binary morphology; unsupervised pattern classification; mathematical morphology operations; multidimensional observations; mathematical discrete binary set; well separated subsets; pattern recognition; set theory
CITATION
J.G. Postaire, R.D. Zhang, C. Lecocq-Botte, "Cluster Analysis by Binary Morphology", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.15, no. 2, pp. 170-180, February 1993, doi:10.1109/34.192490
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