Robust zero watermarking for still and similar images using a learning based contour detection

Digital watermarking is an efficacious technique to protect the copyright and ownership of digital information. Traditional image watermarking algorithms embed a logo in the image that reduces its visual quality. A new approach in watermarking called zero watermarking doesn’t need to embed a logo in the image .in this algorithm we find a feature from the main image and combine it with a logo to obtain a key. This key is securely kept by a trusted authority. IN this paper we show that we can increase the robustness of digital zero water-marking by a new counter detection method in comparison to Canny Edge de-tection and morphological dilatation that is mostly used by related works. Ex-perimental results demonstrate that our proposed scheme is robust against common geometric and non-geometric attacks including blurring, JPEG com-pression, noise addition, Sharpening, scaling, rotation, and cropping. The main advantage of the proposed method is its ability to distinguishable key for imag-es taken from the same scene with small angular rotation and minor displace-ment.