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One of the main challenges in image segmentation is to adapt prior knowledge about the objects/regions that are likely to be present in an image, in order to obtain more precise detection and recognition. Typical applications of such knowledgebased segmentation include partitioning satellite images and microscopy images, where the context is generally well defined. In particular, we present an approach that exploits the knowledge about foreground and background information given in a referencedoi:10.1109/icip.2007.4379521 dblp:conf/icip/BertelliBM07 fatcat:xeforgvkqrhwfouszo22ahexr4