IMPROVING RETRIEVAL EFFECTIVENESS BY INTEGRATED QUERYING OF IMAGES AND TEXT

An integrated retrieval system is developed, enabling simultaneous querying of the image and the text content of a document - a feature not supported by the existing retrieval systems. An integrated query is expressed using the natural language expressions. Image content is queried either based on the color-spatial properties or based on the induced sensations, derived from the color arrangements. The vagueness of the natural language expressions used to query the image content is modeled employing the fuzzy set theory. Integrated retrieval experiment, performed on a database of 1,022 Web pages containing images and text, shows that, when using the integrated queries, the number of retrieved documents in average reduces to 14% of the number obtained by the image or text queries. Image retrieval experiment, involving a database of 1,100 color images and evaluated using a questionnaire involving 10 subjects, shows 70% agreement between the system s and the user s ranking of images. It follows that the proposed integrated querying approach, compared to the conventional image and text querying approaches, enables a more effective retrieval, essential for the large-scale databases like the Internet