Name
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. 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. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1007/s007990050026 | Int. J. on Digital Libraries |
Keywords | Field | DocType |
wavelets,image databases,content-based retrieval,image indexing,feature vector,image processing,wavelet transform,indexation | Feature detection (computer vision),Computer science,Binary image,Image processing,Image retrieval,Artificial intelligence,Top-hat transform,Computer vision,Automatic image annotation,Information retrieval,Pattern recognition,Image texture,Visual Word | Journal |
Volume | Issue | Citations |
1 | 4 | 178 |
PageRank | References | Authors |
16.89 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| James Z. Wang | 1 | 7526 | 403.00 |
| Gio Wiederhold | 2 | 4260 | 1502.89 |
| Oscar Firschein | 3 | 368 | 39.50 |
| Sha Xin Wei | 4 | 251 | 32.82 |