Using Multiple Domain Visual Context in Image Analysis

In this paper we propose an algorithm to improve the results of knowledge-assisted image analysis, based on contextual information. In order to achieve this, we utilize fuzzy algebra, fuzzy sets and relations, towards efficient manipulation of image region concepts. We provide a novel context modelling, based on the OWL language, using RDF reification. Initial image analysis results are enhanced by the utilization of domain-independent, semantic knowledge in terms of concepts and relations between them. The novelty of the presented work is the context-driven re-adjustment of the degrees of confidence of the detected concepts produced by any image analysis technique, utilizing a domain-independent ontology infrastructure to handle the knowledge, as well as multiple application domains.