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dc.creatorTasoulis, S. K.en
dc.creatorDoukas, C. N.en
dc.creatorMaglogiannis, I.en
dc.creatorPlagianakos, V. P.en
dc.date.accessioned2015-11-23T10:49:32Z
dc.date.available2015-11-23T10:49:32Z
dc.date.issued2010
dc.identifier10.1007/978-3-642-12842-4_28
dc.identifier.isbn3642128416
dc.identifier.issn3029743
dc.identifier.urihttp://hdl.handle.net/11615/33569
dc.description.abstractIn this paper we propose a clustering technique for the recognition of pigmented skin lesions in dermatological images. It is known that computer vision-based diagnosis systems have been used aiming mostly at the early detection of skin cancer and more specifically the recognition of malignant melanoma tumour. The feature extraction is performed utilising digital image processing methods, i.e. segmentation, border detection, colour and texture processing. The proposed method belongs to a class of clustering algorithms which are very successful in dealing with high dimensional data, utilising information driven by the Principal Component Analysis. Experimental results show the high performance of the algorithm against other methods of the same class. © Springer-Verlag Berlin Heidelberg 2010.en
dc.source.urihttp://www.scopus.com/inward/record.url?eid=2-s2.0-78650502238&partnerID=40&md5=774543ea328ed4f8c7ee5d510428b0df
dc.subjectClassificationen
dc.subjectCluster analysisen
dc.subjectFeature extractionen
dc.subjectImage analysisen
dc.subjectKernel density estimationen
dc.subjectPigmented skin lesionen
dc.subjectPrincipal Component Analysisen
dc.subjectUnsupervised clusteringen
dc.subjectPigmented skin lesionsen
dc.subjectPrincipal Componentsen
dc.subjectArtificial intelligenceen
dc.subjectComputer visionen
dc.subjectDermatologyen
dc.subjectImage segmentationen
dc.subjectProcessingen
dc.subjectClustering algorithmsen
dc.titleSkin lesions characterisation utilising clustering algorithmsen
dc.typeotheren


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