In 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.
CITATION STYLE
Tasoulis, S. K., Doukas, C. N., Maglogiannis, I., & Plagianakos, V. P. (2010). Skin lesions characterisation utilising clustering algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6040 LNAI, pp. 243–253). https://doi.org/10.1007/978-3-642-12842-4_28
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