Effective ways for querying images by content over the Internet

Increasing numbers of images have made explicit the need for more effective and efficient image indexing and searching of not only the meta-data associated with an image but also retrieval directly based on the content of the image. The scope of the COBWEB (COntext-Based image retrieval on the WEB) project (EP28773) is to create a pioneer system that provides a solution to the problem of automatically storing and retrieving images from large image databases dispersed over the Internet. The project focuses on the following issues. (i) Development of effective algorithms for automatic storage of the visual features of the images, which can be used as a means for retrieving similar images. (ii) Creation of a simple, cross-platform user interface that helps the user to query the database in the most natural way. (iii) Development of a robust communication subsystem that guarantees satisfying retrieval times. In this paper, we describe the architecture and implementation details of the human-computer interface (HCI) and the intelligent search component (ISC), which are two of the main components of the COBWEB system. The HCI consists of a graphical interface, which enables the user to interact with the system. It provides the user with various approaches in querying the database, including keyword specification and sample image submission. The ISC´s main tasks are to handle and translate the query criteria submitted by the user through the HCI, to navigate the database and find images that satisfy those criteria, and to return the results to the HCI