Refereed full papers (journals, book chapters, international conferences)

1997

@inproceedings{WWF1997,
	vgclass =	{refpap},
	vgproject =	{cbir},
	author =	{Ze~Wang, James and Gio Wiederhold and Oscar Firschein and
	Xin Wei, Sha},
	title =	{Wavelet-Based Image Indexing Techniques with Partial
	Sketch Retrieval Capability},
	booktitle =	{Proceedings of the Fourth Forum on Research and Technology
	Advances in Digital Libraries},
	address =	{Washington D.C.},
	pages =	{13--24},
	month =	{May},
	year =	{1997},
	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.},
}