Content-based Image Indexing and Searching
Using Daubechies' Wavelets

James Ze Wang, Gio Wiederhold, Oscar Firschein, Sha Xin Wei
Stanford University, Stanford, CA 94305
Abstract:

This paper describes WBIIS (Wavelet-Based Image Indexing and Searching), a new image indexing and retrieval algorithm with partial sketch image searching capability for large image databases. The algorithm characterizes the color variations over the spatial extent of the image in a manner that provides semantically-meaningful image comparisons. The indexing algorithm applies a Daubechies' wavelet transform for each of the three opponent color components. The wavelet coefficients in the lowest few frequency bands, and their variances, are stored as feature vectors. To speed up retrieval, a two-step procedure is used that first does a crude selection based on the variances, and then refines the search by performing a feature vector match between the selected images and the query. For better accuracy in searching, two level multiresolution matching may also be used. Masks are used for partial-sketch queries. This technique performs much better in capturing coherence of image, object granularity, local color/texture, and bias avoidance than traditional color layout algorithms. When tested on a database of more than 10,000 general-purpose images, WBIIS is much faster and more accurate than traditional algorithms.


Full Paper in Color

(PDF)    (PDF and PostScript, from Springer)

Try a Simplified Demo Search

Web Page of the Article at Springer


Citation: James Z. Wang, Gio Wiederhold, Oscar Firschein and Sha Xin Wei, ``Content-Based Image Indexing and Searching Using Daubechies' Wavelets,'' International Journal on Digital Libraries, vol. 1, no. 4, pp. 311-328, Springer-Verlag, 1998.

Copyright 1998 Springer-verlag. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the Springer-verlag.

Last Modified: Mon Aug 4 13:13:45 PDT 1997
© 1997, James Z. Wang