A Robust Watermark Algorithm Based on Ridgelet Transform and Fuzzy C-Means
Haiyan Yu, Jiulun Fan, Xiaoli Zhang · 2009
Combining the human visual system with the image local properties, this paper proposes a novel watermarking algorithm based on ridgelet transform and fuzzy c-means (FCM) clustering. In order to obtain a sparse representation of the image, especially for straight edge singularity, the image is first partitioned into small pieces and the ridgelet transform is applied for each piece. The image pieces are adaptively classified into frat regions and texture regions by applying FCM clustering algorithm through analyzing texture distribution in ridgelet coefficients of each piece. And the watermarking is embedded into the middle ridgelet subband in the highest energy directions of texture pieces, where the embedding strength is also adjusted by the analysis of ridgelet coefficients of each piece based on the feature of luminance masking and texture masking. Then the embedded watermark can be blindly detected by correlation detector. Experimental results prove robustness and transparency of the proposed watermarking scheme.