Algorithms for reducing the semantic gap in image retrieval systems

In this paper we study the possibilities to discover correlations between visual primitive characteristics and semantic concepts of images, meaning the extraction of semantic meaning based on learning, from an image database. The problem of automatic discovery of semantic inference rules is approached. A semantic rule is a combination of semantic indicator values, which are visual elements, that identifies semantic concepts of images. The annotation procedure starts with the semantic rules generation on each image category. The language used for rules representation is Prolog. The advantages of using Prolog are its flexibility and simplicity in representation of rules. Our methods are not limited to any specific domain and they can be applied in any field.