Feature extraction and local Zernike moments based geometric invariant watermarking
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A robust and geometric invariant digital image watermarking scheme based on robust feature detector and local Zernike transform is proposed in this paper. The robust feature extraction method is proposed based on the Scale Invariant Feature Transform (SIFT) algorithm, to extract circular regions/patches for watermarking use. Then a local Zernike moments-based watermarking scheme is raised, where the watermarked regions/patches can be obtained directly by inverse Zernike Transform. Each extracted circular patch is decomposed into a collection of binary patches and Zernike transform is applied to the appointed binary patches. Magnitudes of the local Zernike moments are calculated and modified to embed the watermarks. Experimental results show that the proposed watermarking scheme is very robust against geometric distortion such as rotation, scaling, cropping, and affine transformation; and common signal processing such as JPEG compression, median filtering, and low-pass Gaussian filtering.
KeywordsGeometric invariant Feature extraction SIFT Local Zernike transform Inverse Zernike transform
The authors would like to thank the referees for their valuable comments. This work was supported in part by the Science and Technology Development Fund of Macau SAR (Project No. 034/2010/A2) and the Research Committee of the University of Macau.
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