Image understanding and scene models: a generic framework integrating domain knowledge and Gestalt theory
Because of the semantic gap between low-level descriptors and semantic concepts, image understanding systems need to use domain knowledge in order to map regions of a segmented image into semantic objects. However, such systems are often strongly dependent on an application since domain knowledge is not separated from procedures. We therefore argue for a generic grouping mechanism, based on the vision procedures of Gestalt theory, able to evaluate the relevance of its groupings with domain knowledge. In order to be used in a flexible way, such domain knowledge is stored independently in ontologies. We emphasize the need for domain knowledge to be thought as scene knowledge on a multilevel of composition, in order to be efficiently used. We also present the whole framework of our system and an application example within a specific domain: image understanding of thessalian graves' images.