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Efficient and Effective Querying by Image Content (1994)
| Venue: | Journal of Intelligent Information Systems |
| Citations: | 495 - 13 self |
BibTeX
@ARTICLE{Faloutsos94efficientand,
author = {C. Faloutsos and W. Equitz and M. Flickner and W. Niblack and D. Petkovic and R. Barber},
title = {Efficient and Effective Querying by Image Content},
journal = {Journal of Intelligent Information Systems},
year = {1994},
volume = {3},
pages = {231--262}
}
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Abstract
In the QBIC (Query By Image Content) project we are studying methods to query large on-line image databases using the images' content as the basis of the queries. Examples of the content we use include color, texture, and shape of image objects and regions. Potential applications include medical ("Give me other images that contain a tumor with a texture like this one"), photo-journalism ("Give me images that have blue at the top and red at the bottom"), and many others in art, fashion, cataloging, retailing, and industry. We describe a set of novel features and similarity measures allowing query by color, texture, and shape of image object. We demonstrate the effectiveness of the QBIC system with normalized precision and recall experiments on test databases containing over 1000 images and 1000 objects populated from commercially available photo clip art images, and of images of airplane silhouettes. We also consider the efficient indexing of these features, specifically addre...
Keyphrases
image content effective querying image object many others novel feature similarity measure potential application airplane silhouette qbic system efficient indexing test database normalized precision available photo clip art image include color recall experiment large on-line image database
