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

Abstract

A texture descriptor invariant to translation, rotation and scale changes is presented in this paper. A power spectral image is obtained by using the DFT 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.