30 KB581 KB20 KB200020242003Lezoray, Olivierštevilka:2letnik:228 stranistr. 113-120ISSN:1580-3139COBISSID:16596185URN:URN:NBN:SI:doc-K1SEOOQNenDruštvo za stereologijo in kvantitativno analizo slike, Medicinska fakultetaImage analysis and stereologyagregatianaliza slikBarvabarveColorImage Processing, Computer-AssistedsegmentacijaSlika, obdelava z računalnikomSupervised automatic histogram clustering and watershed segmentation. Application to microscopic medical color images|In this paper, an approach to the segmentation of microscopic color images is addressed, and applied to medical images. The approach combines a clustering method and a region growing method. Each color plane is segmented independently relying on a watershed based clustering of the plane histogram. The marginal segmentation maps intersect in a label concordance map. The latter map is simplified based on the assumption that the color planes are correlated. This produces a simplified label concordance map containing labeled and unlabeled pixels. The formers are used as an image of seeds for a color watershed. This fast and robust segmentation scheme is applied to several types of medical imagesTEXTznanstveno časopisjejournalsSlovenian National E-content AggregatorNational and University Library of SloveniaDruštvo za stereologijo in kvantitativno analizo slike