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Color and texture induced structures of keyword space

The amount of available digital information is growing very fast and the development of tools to handle these huge amounts of information is currently among the hottest research topics. The most popular and powerful engines (like Google) are text-based but research on the development of search engines dealing with visual information is receiving more and more attention. Traditional approaches use keywords to describe an image and text-based engines for searching the database. This is however difficult, costly, time consuming and the result depends on the subjective judgement of the creator of the keyword database. Automatic extraction of image content features and content-based search has thus received a lot of attention recently. We have developed several versions of a fast browser that uses color and textural properties of images to browse a very large online image database. In this paper we will describe some features of this browser and we will describe our experiments in which we use color and texture based similarity measures to explore structures in a corresponding set of keywords that are used to index the images in the database.