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Content-based Image Indexing and Searching Using Daubechies' Wavelets

Wang, J. and Wiederhold, G. and Firschein, O. and Wei, S. (1998) Content-based Image Indexing and Searching Using Daubechies' Wavelets. International Journal on Digital Libraries (IJODL), 1 (4). pp. 311-328.




This paper describes WBIIS (Wavelet-Based Image Indexing and Searca 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 semanticallymeaningful image comparisons. The indexing algorithm applies a Daubechies' wavelet transform for each of the three opponent color components. The wavelet coeffcients 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 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 uch better in capturing coherence of image, object granularity, local color/texture, and bias avoidance than traditional color layout algorithms. WBIIS is much faster and more accurate than traditional algorithms. When tested on a database of more than 10,000 general-purpose images, the best 100 matches were found in 3.3 seconds. Key words: Content-based Retrieval { Image Databases { Image Indexing { Wavelets

Item Type:Article
Uncontrolled Keywords:content based image retrieval, wavelet, WBIIS
Subjects:Computer Science > Image Processing
Projects:Image Database
Related URLs:Project Homepage
ID Code:359
Deposited By:Import Account
Deposited On:25 Feb 2000 16:00
Last Modified:29 Dec 2008 12:13

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