39 KB248 KB23 KB200020242001Kervrann, Charlesletnik:20številka:36 stranistr. 163-168ISSN:1580-3139COBISSID:16036313URN:URN:NBN:SI:doc-FFANV0FPenDruštvo za stereologijo in kvantitativno analizo slike, Medicinska fakultetaImage analysis and stereologyanaliza slikBayes TheoremBayesov teoremImage Processing, Computer-AssistedporazdelitevSlika, obdelava z računalnikomstereologijaBayesian image segmentation through level lines selection|Bayesian statistical theory is a convenient way of taking a priori informationinto consideration when inference is made from images. In Bayesian image segmentation, the a priori distribution should capture the knowledge about objects. Taking inspiration from (Alvarez et ad., 1999), we design a prior density that penalizes the area of homogeneous parts in images. The segmentation problem is further formulated as the estimation of the set of curves that maximizes the posterior distribution. In this paper, we explore a posterior distribution model for which its maximal mode is given by a subset of level curves, that is the boundaries of image level sets. For the completeness of the paper, we present a stepwise greedy algorithm for computing partitions with connected componentsTEXTznanstveno časopisjejournalsSlovenian National E-content AggregatorNational and University Library of SloveniaDruštvo za stereologijo in kvantitativno analizo slike