32 KB555 KB21 KB200020242004Huang, Jian-JunTang, LiangXie, Wei-Xinštevilka:1letnik:239 stranistr. 23-31ISSN:1580-3139COBISSID:20714969URN:URN:NBN:SI:doc-7XD2OHKAenDruštvo za stereologijo in kvantitativno analizo slike, Medicinska fakultetaImage analysis and stereologyFuzzy LogicImage Processing, Computer-AssistedMehka logikaobdelava slikSlika, obdelava z računalnikomstereologijaAutomatic multilevel image segmentation based on fuzzy reasoning|An automatic multilevel image segmentation method based on sup-star fuzzy reasoning (SSFR) is presented. Using the well-known sup-star fuzzy reasoning technique, the proposed algorithm combines the global statistical information implied in the histogram with the local information represented by the fuzzy sets of gray-levels, and aggregates all the gray-levels into several classes characterized by the local maximum values of the histogram. The presented method has the merits of determining the number of the segmentation classes automatically, and avoiding to calculating thresholds of segmentation. Emulating and real image segmentation experiments demonstrate that the SSFR iseffectiveTEXTznanstveno časopisjejournalsSlovenian National E-content AggregatorNational and University Library of SloveniaDruštvo za stereologijo in kvantitativno analizo slike