I think it is possible to embed invisible information into videos and images. This way peopple could track where you got an image from, the source from which you copied it, and people who copy your image to share it again. https://github.com/ShieldMnt/invisible-watermark

Services like youtube or twitter could embed such watermarks into content they serve to specific users without them knowing; Smartphone-cameras could mark images in secret.

I guess blurring, rotating or dithering the image could destroy watermarks. Or maybe just sharing a screenshot of an image instead of the original image. Format conversions may help too.

Keywords: digital-watermarking. tracking.

  • PowerCrazy@lemmy.mlEnglish
    1·
    2 hours ago

    It’s something to be aware of if you are trying to record/send images in secret. But it’s not a problem if you are passing on an image you found somewhere else. You leave no trace if you are just passing the image, so the image itself is of no concern privacy-wise.

  • brownmustardminion@lemmy.ml
    14·
    9 hours ago

    Most people don’t know your photos can be cross profiled and identified by the unique noise signature of your camera.

    I’ve never heard of it being used in practice though. There’s a github repo somewhere if you’re interested in trying it yourself.

    • greenbelt@lemy.lolOP
      5·
      11 hours ago

      Not necessarily, a qr-code can still work even if you compress it, due to digital error-correction mechanisms in the code.

        • Telex@sopuli.xyz
          4·
          10 hours ago

          One might think that watermarks are designed to resist corruption as well. But I have no idea.

          • MoonMelon@lemmy.mlEnglish
            3·
            7 hours ago

            They are, if you scroll to the bottom of the github repo that OP posted there are some examples of what works and doesn’t work to break it.

            Watermark data like this is stored in the least significant bits of the pixels themselves, or in the case of OPs example, they do a frequency decomposition on the image then store the watermark data in the coefficients. Basically you have to trash the pixel data at least a little bit to defeat it. So cropping or flipping the image won’t do it, but resizing or rotating with some kind of filtering will.

            I have no idea how the machine-learning technique listed there is working, and their documentation link is broken :(