Query by Image Content (QBIC)
Dragutin Petkovic
Manager, Advanced Algorithms, Architectures and Applications
IBM Almaden Research Center
Abstract
The QBIC (Query By Image Content) project at IBM's Almaden Research
Center is studying methods to query large on-line image databases
using the images' content as the basis of the queries. Examples of
the content used include color, texture, shape, size, orientation, and
position of image objects and regions. Key issues include derivation
and computation of attributes of images and objects that provide
useful query functionality, retrieval methods based on similarity as
opposed to exact match, query by image example or user drawn image,
the user interfaces, query refinement and navigation, high dimensional
database indexing, and automatic and semi-automatic database
population. We currently have a prototype system written in X/Motif
and C running on an RS/6000 that allows a variety of queries, and a
test database of over 2000 images and 2000 objects populated from
commercially available photo clip art images. The QBIC technology is
a basis for recently announced product called Ultimedia Manager
1.1. The key applications of this technology are in the areas where
image patterns are the basis of the queries, like in retail
cataloging, stock photo archives, art, business graphics and certain
medical applications. For example, this technology is used by UC
Davis Art Library (Prof. B. Holt) to answer queries like "Give me all
artists that use brush strokes like Van Gough" which were not possible
to answer using standard keyword search methods.
In this talk we will also show a demo of the Ultimedia Manager 1.1
product that combines QBIC technology with the traditional SQL search.
The work has been done by the team form IBM Almaden Research Center
(project leader Wayne Niblack) and with IBM Santa Teresa Lab
(product manager Frank Tung).