Google new software can easily remove watermarks from photos
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Google’s research division showed earlier this week how easy is for computer algorithms to erase standard photo watermarking, making images vulnerable to reposting across the internet without credit.
The tech giant’s researchers based their discovery on the findings of the computer vision conference CVPR in Hawaii back in July, described in a paper titled “On the Effectiveness of Visible Watermarks.”
“Visible watermarks are often designed to contain complex structures such as thin lines and shadows in order to make them harder to remove,” they said.
“However, a fact that has been overlooked so far is that watermarks are typically added in a consistent manner to many images. We show that this consistency can be used to invert the watermarking process.
“This can all be done automatically, without any user intervention or prior information about the watermark, and by only observing watermarked image collections publicly available online.”
In other words, experts behind the watermark-removal software were able to train software with enough public samples to identify common watermark techniques and then, through a process called “multi-image matting,” separate the watermark’s components from the rest of the image.
“We found that introducing random geometric perturbations to the watermark — warping it when embedding it in each image — improves its robustness. Interestingly, very subtle warping is already enough to generate watermarks that this technique cannot fully defeat.”
“This warping produces a watermarked image that is very similar to the original (top right in the following figure), yet now if an attempt is made to remove it, it leaves very visible artifacts (bottom right):”
The team admits that the method is not a perfect one.
However, they believe that “While we cannot guarantee that there will not be a way to break such randomized watermarking schemes in the future, we believe (and our experiments show) that randomization will make watermarked collection attacks fundamentally more difficult.
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“We hope that these findings will be helpful for the photography and stock image communities.”