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Context based retrieval on the web

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Résultats exploitables

The increasing volumes of images have created the need for more effective and efficient image indexing and searching, not only of the metadata associated with an image (e.g. captions, annotations) but also retrieval based directly on the content of the image. COBWEB is a pioneer system that will provide a solution to the problem of automatically storing and retrieving images from large image databases dispersed over the Internet. For this purpose, the project focused on the development of effective algorithms for the automatic indexing of the visual features of imagery (e.g. colour, texture) that can be used as a means for retrieving similar images without the burden of manual indexing, although the ultimate objective is semantic based access to images. A second important issue about COBWEB is the creation of a simple, useful and effective user interface. The interface will hide the system's internal complexity (e.g. feature extraction and indexing algorithms, search procedures) from the end-user and will help the user perform queries and retrieve images in the most "natural" way. Therefore, the user interface will provide retrieval tools, designed to match the human way of thinking. Having in mind that the client's location may be remote, referring to the database's location, the above goals should be achieved in the most effective way, as far as time and costs are concerned. Thus, the architecture of the system in terms of communication between the various components is another quite important subject. The main objectives of COBWEB are: -To reduce the time and costs to store a new image in an existing image database. This will be achieved by dramatically reducing the need for textual annotation of image. -To reduce the time and costs to retrieve an image from an existing image database. This will be achieved by dramatically increasing the precision of the retrieval process.

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