Translation, scale, and rotation invariant texture descriptor for texture-based image retrieval

被引：14
|
作者：
Sim, DG [1 ]
Kim, HK [1 ]
Oh, DI [1 ]
机构：
[1] Hyundai Elect Ind Co Ltd, Seocho Ku, Seoul, South Korea
来源：
2000 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL III, PROCEEDINGS | 2000年
关键词：
D O I：
10.1109/ICIP.2000.899561
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A texture descriptor invariant to translation, rotation and scale changes is presented in this paper. A power spectral image is obtained by using DFT transformation to extract the proposed descriptor for the translation invariance of a given texture. The power spectral image is scale-normalized by a cut-off frequency on the power spectral image that is calculated as the total energy inside a circle with its radius of the cut-off frequency amounts to a predetermined value. Finally, the rotation invariant Zernike moments are calculated on the translation and scale normalized image for a rotation, scale and translation invariant descriptor. The extraction is simple and fast, using fast known DFT and Zernike transformation. The matching is also simple and fast using the Euclidean distance measure between a query and test textures. The effectiveness of the proposed algorithm is shown with various texture databases.
引用
收藏
页码：742 / 745
页数：4
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