FIDS

(Flexible Image Database System)

Developer

Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA.

URL

http://www.cs.washington.edu/research/imagedatabase/.

References

[BS99].

Features

FIDS uses the following features. The color histogram, and the fraction of flesh colored pixels. The histogram of values after applying the Sobel edge filter. The local binary pattern histogram. The coefficients of the Haar wavelet decomposition. These features are also taken of subimages in a grid, in rows, and columns.

Querying

The user chooses an image as query image. He can select the feature distance measures, and combine them into an overall distance measure. A result image can be used as next query image.

Matching

The distances between the histograms are the L₁-distance. The distance between wavelet coefficients, is some weighted difference. An overall distance can be composed by taking the weighted sum, maximum, or minimum of the individual feature distances, which preserves metric properties.

Indexing

In a preprocessing step, the distance of all database objects to m reference objects are computed, and stored in a so-called trie structure [E.F60]. At query time, the distances d_i, $i=1,\ldots,m$ of the query to these reference objects are also computed. These both distances and the triangle inequality are used to establish a lower bound on the distance between the query and the database images. The trie structure is used to filter the database images on this lower bound.

Result presentation

The images can be ordered on their lower bound, so that no exact distances between query and images need to be calculated. Alternatively, the user can select of how many of those the true distance must be calculated.