Name
Abstract | ||
|---|---|---|
This paper proposes a novel texture feature extraction technique for texture image retrieval. The method is robust to geometric distortions as well as noise effect. The geometric distortions include rotation, scaling and translation modifications of textures. In the feature extracting process, log-polar transformed autocorrelation images are introduced to eliminate the effects of the entire distortions. The influence of additive noise is reduced by modifying autocorrelation images. In the retrieval process, valuable wavelet packet statistics is used to measure similarity between individual images. The effectiveness of our method is demonstrated using noisy distorted texture image database in the experimental simulations. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/ICIP.2005.1529803 | ICIP (1) |
Keywords | DocType | Volume |
wavelet packet statistics,statistics,geometric distortions,wavelet transforms,log-polar transformed autocorrelation images,texture retrieval,geometric distortion,robust feature extraction technique,feature extraction,image retrieval,robust,log-polar transform,image texture,texture image retrieval,additive noise | Conference | 1 |
ISSN | ISBN | Citations |
1522-4880 | 0-7803-9134-9 | 5 |
PageRank | References | Authors |
1.39 | 7 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhuo Liu | 1 | 118 | 16.03 |
| Shigeo Wada | 2 | 24 | 11.06 |