A novel image watermarking scheme based on support vector regression

In this paper, a novel support vector regression based color image watermarking scheme is proposed. Using the information provided by the reference positions, the support vector regression can be trained at the embedding procedure, and the watermark is adaptively embedded into the blue channel of the host image by considering the human visual system. Thanks to the good learning ability of support vector machine, the watermark can be correctly extracted under several different attacks. Experimental results show that the proposed scheme outperform the Kutter's method and Yu's method against different attacks including noise addition, shearing, luminance and contrast enhancement, distortion, etc. Especially when the watermarked image is enhanced in luminance and contrast at rate 70%, our method can extract the watermark with few bit errors.