VIR Image Engine

The VIR Image Engine is an extensible framework for building content based image retrieval systems.

Developer

Virage Inc.

URL

http://www.virage.com/products/vir-irw.html.

References

[BFG⁺96].

Features

A basic concept is that of a primitive, which denotes a feature's type, computation and matching distance. Five abstract data types are defined: global values and histograms, local values and histograms, and graphs. The VIR Image Engine provides a set of general primitives, such as global color, local color, texture and shapes. Appart from these, various domain specific primitives can be created when developing an application. When defining such a primitive, the developer supplies a function for computing the primitive's feature data from the raw image.

Querying and Result presentation

The VIR Image Engine provides a set of GUI tools necessary for the development of a user interface. These include facilities for image insertion, image query, weight adjustment for re-query, inclusion of keywords, and support for several popular image file formats. Another available component, the query canvas, allows queries-by-sketch; it consists of a bitmap editor where the user can sketch a picture with drawing tools and color it using the colors from a palette. Also, the user can bring onto the canvas an image from an existing collection and modify it using the same drawing tools. Queries can be performed on various user-defined combinations of primitives.

Matching

When defining a new primitive, a function for computing the similarity between two sets of feature data previously extracted must also be supplied by the developer. When comparing two images, for each primitive in the current query combination, a similarity score is computed using the distance function defined within the primitive. These individual scores are combined in an overall score using a set of weights in a way characteristic to the application. This score is then stored in a score structure, which contains also the individual similarity scores for each primitive. This allows a quick recomputation of the overall score for a new set of weights.

Relevance feedback

A sort of relevance feedback is obtained by searching for matches to a fixed query image for different sets of weights.

Indexing

The storage of feature data for all primitives is the responsibility of the application developer.

Applications

The system was integrated into databases from Sybase, Object Design, and Objectivity, and added as a component to the Oracle DBMS. Two applications of Virage technology are the AltaVistaAltaVista Photofinder and Illustra's Visual Intelligence system.