Semantic-Friendly Indexing and Quering of Images Based on the Extraction of the Objective Semantic Cues

摘要

Abstract image semantics resists all forms of modeling, very much like any kind of intelligence does. However, in order to develop more satisfying image navigation systems, we need tools to construct a semantic bridge between the user and the database. In this paper we present an image indexing scheme and a query language, which allow the user to introduce cognitive dimension to the search. At an abstract level, this approach consists of: (1) learning the “natural language” that humans speak to communicate their semantic experience of images, (2) understanding the relationships between this language and objective measurable image attributes, and then (3) developing corresponding feature extraction schemes.