Clustering Techniques for Marbles Classification

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dc.creatorCaldas-Pinto, J. R.
dc.creatorPina, Pedro
dc.creatorRamos, Vitorino
dc.creatorRamalho, Mario
dc.date2004-12-17
dc.date.accessioned2026-07-25T16:52:03Z
dc.descriptionAutomatic marbles classification based on their visual appearance is an important industrial issue. However, there is no definitive solution to the problem mainly due to the presence of randomly distributed high number of different colours and its subjective evaluation by the human expert. In this paper we present a study of segmentation techniques, we evaluate they overall performance using a training set and standard quality measures and finally we apply different clustering techniques to automatically classify the marbles. KEYWORDS: Segmentation, Clustering, Quadtrees, Learning Vector Quantization (LVQ), Simulated Annealing (SA).
dc.description7 pages, 17 figures, at http://alfa.ist.utl.pt/~cvrm/staff/vramos/ref_41.html
dc.identifierhttps://arxiv.org/abs/cs/0412076
dc.identifierhttp://arxiv.org/abs/cs/0412076
dc.identifierRecPad 2002 -12th Portuguese Conference on Pattern Recognition, ISBN 972-789-067-9, Aveiro, Portugal, June 27-28, 2002
dc.identifier.urihttps://dspace.dare.co.zw/handle/123456789/43723
dc.subjectArtificial Intelligence
dc.subjectComputer Vision and Pattern Recognition
dc.subjectI.2; I.5
dc.titleClustering Techniques for Marbles Classification
dc.typetext

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