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This is just adding a warping effect, and I’m quite sure that if this technology had already existed, then the same team at Google that did this research would

This is just adding a warping effect, and I’m quite sure that if this technology had already existed, then the same team at Google that did this research would have, with a similar amount of work, been able to circumvent this technique, too. I mean, de-warping warped imagery is something that Google’s image stabilization software used on YouTube can already do very well. Adapting it for this purpose should be possible.

awaythrow101 9y ago
But wouldn't it require you to find how the target image's particular watermark was warped? None of the other watermarks will have precisely the same warping parameters as that image's watermark. You could attempt to de-warp the watermark in place on the image, but that would seem to be likely to warp the image as well, no?
- woodrowbarlow 9y ago
  you could de-warp the watermark in place, and this would warp the image but you could reverse the warp after you're done removing the watermarks.
pps43 9y ago
If the same watermark is added to each image, then you can estimate the watermark by averaging many images and subtract it to get original image back. If each image has a slightly different watermark, then simple averaging won't work. Instead you need to come up with a model that describes how the watermark is changing, then estimate parameters of that model. The more complex the change, the more images you need for parameter estimation. Image stabilization won't work here because it relies on large features and therefore won't be sensitive to relatively weak watermark signal. Besides, it's only stabilizing in three dimensions (pitch, roll, yaw) and won't help with warping within the image.
- Retric 9y ago
  Averaging will still provide the average watermark given a large enough sample set. Which is then a single geometric transformation from the used watermark. Estimating that transformation for a specific image should be fairly straightforward as they could easily reverse a watermark that was offset. At which point it's reversible.
  - pps43 9y ago
    Not really, because in each image parts of the watermark will be in different places. You don't even need to warp the watermark to achieve that, it's enough to randomly reposition it.
    - Retric 9y ago
      Supose you have 4 points on a box. If you randomly increase or decrease the location of each point by some random value say +-3% then averaged 100,000 of those boxes, you get a smaller box(1) surrounded by a larger increasingly blurry box. This is true even if no single picture shows that single smaller box, but it will show up on the average. (1) Rather than a true box the midpoints are going to be slightly buldging, but with a large sample set it's very close to a box. Sure, you can get into cat and mouse games ever stranger geometry. But, the water mark is limited by how much it distracts from the image.
      - pps43 9y ago
        The article shows the result of this approach, and it clearly does not work well.
        Retric 9y ago
        As I said you need a new step: "Estimating that transformation for a specific image should be fairly straightforward". It does show a good average and simply moving the watermark was easily reversible suggesting detection of a watermark in an image was easy.
    - 9y ago
AndrewCHM 9y ago
straightening a plane e.g. a whole video frame, is a bit different from removing a random warp on a watermark (where the warp is more complex than tilting/angling the watermark), while its overlaid with partial visibility on a non-warped image

awaythrow101 9y ago

But wouldn't it require you to find how the target image's particular watermark was warped? None of the other watermarks will have precisely the same warping parameters as that image's watermark. You could attempt to de-warp the watermark in place on the image, but that would seem to be likely to warp the image as well, no?

woodrowbarlow 9y ago
you could de-warp the watermark in place, and this would warp the image but you could reverse the warp after you're done removing the watermarks.

pps43 9y ago

If the same watermark is added to each image, then you can estimate the watermark by averaging many images and subtract it to get original image back. If each image has a slightly different watermark, then simple averaging won't work. Instead you need to come up with a model that describes how the watermark is changing, then estimate parameters of that model. The more complex the change, the more images you need for parameter estimation. Image stabilization won't work here because it relies on large features and therefore won't be sensitive to relatively weak watermark signal. Besides, it's only stabilizing in three dimensions (pitch, roll, yaw) and won't help with warping within the image.

Retric 9y ago
Averaging will still provide the average watermark given a large enough sample set. Which is then a single geometric transformation from the used watermark. Estimating that transformation for a specific image should be fairly straightforward as they could easily reverse a watermark that was offset. At which point it's reversible.
- pps43 9y ago
  Not really, because in each image parts of the watermark will be in different places. You don't even need to warp the watermark to achieve that, it's enough to randomly reposition it.
  - Retric 9y ago
    Supose you have 4 points on a box. If you randomly increase or decrease the location of each point by some random value say +-3% then averaged 100,000 of those boxes, you get a smaller box(1) surrounded by a larger increasingly blurry box. This is true even if no single picture shows that single smaller box, but it will show up on the average. (1) Rather than a true box the midpoints are going to be slightly buldging, but with a large sample set it's very close to a box. Sure, you can get into cat and mouse games ever stranger geometry. But, the water mark is limited by how much it distracts from the image.
    - pps43 9y ago
      The article shows the result of this approach, and it clearly does not work well.
      - Retric 9y ago
        As I said you need a new step: "Estimating that transformation for a specific image should be fairly straightforward". It does show a good average and simply moving the watermark was easily reversible suggesting detection of a watermark in an image was easy.
  - 9y ago

AndrewCHM 9y ago

straightening a plane e.g. a whole video frame, is a bit different from removing a random warp on a watermark (where the warp is more complex than tilting/angling the watermark), while its overlaid with partial visibility on a non-warped image