When I want to redact something on a photo, I just draw a rectangle over it, and fill it with the background color. There's no recovering from that.
Recovering redacted information from pixelated videos
51–60 of 70 posts
Re: Recovering redacted information from pixelated videos
#52Earlier quoted context omitted.
That probably isn't very useful since the video isn't moving.
With a redaction as bad as a Gaussian blur at such a high resolution (and a dictionary of only 2048 candidates), you don't need multiple angles to decipher those words. It'd be great if they replaced the key with bogus words first before blurring to troll people, but somehow I doubt it.
> It'd be great if they replaced the key with bogus words first before blurring to troll people, but somehow I doubt it.
This is what I do 99% of the time I use blur to censor information; just replace the text with, say, colorful words of the same length before blurring. Would be neat if there was an automated tool that could do something similar.
Re: Recovering redacted information from pixelated videos
#53When I want to redact something on a photo, I just draw a rectangle over it, and fill it with the background color. There's no recovering from that.
yet ;)
Re: Recovering redacted information from pixelated videos
#54Earlier quoted context omitted.
I recently made use of my right to access personal information from someone who had sent me unsolicited marketing material. The person who fulfilled my request sent me a PDF copy of their full customer list, where all entries had been blacked out except mine. As you may anticipate, that blacking out was simply a black box drawn on top of the actual data. It took me all of 3 seconds to select all, copy, then paste in…
About 10 years ago or something, someone in the US government made this mistake and it was all over the news. That’s when a redaction tool suddenly appeared in Adobe Acrobat.
I thought at that point they started to print out the redacted versions and scanned them again.
Re: Recovering redacted information from pixelated videos
#55As University libraries have moved online, one reads many poorly scanned journal articles. I often wonder about taking the time to clean them up. What replaces temporal information here is the same characters appearing over and over. So of course I read this article hoping to learn about an off-the-shelf tool that would do a great job of scanned text reconstruction. Alas, the best candidates were "no code available."
Not off the shelf but here are some tools. I have no experience with them. Wolf binarization - I think it makes the text more clear before OCR. https://github.com/chriswolfvision/local_adaptive_binarizati... This thing OCRs the pdf using Tesseract OCR https://github.com/ocrmypdf/OCRmyPDF/ Two other pdf tools https://github.com/qpdf/qpdf https://github.com/pikepdf/pikepdf
I'll play with the Wolf filter, thanks.
Math typesetting is too messy for current OCR tools. It would be nice to reverse-engineer the LaTeX source for a math paper, but not likely soon. OCR for the language would help in mind-mapping a web connecting my saved papers, but I wouldn't use it for reading.
I want everything to look like a 600dpi scan mixed down, as I would make, rather than what the libraries thought would be acceptable. For the pure joy of reading.
The easiest approach that might work would be language agnostic, understanding only what clean scans of characters look like. Can we back-solve a clean scan from a lower resolution mess, matching up similar characters in the text without identifying the characters?
Somehow I imagine this is a giant singular value problem. I'm ok if it takes a day to run per paper, I have spare machines.
Re: Recovering redacted information from pixelated videos
#56When I want to redact something on a photo, I just draw a rectangle over it, and fill it with the background color. There's no recovering from that.
Unless a thumbnail was embedded in the exif data, and wasn't updated in the software you used to draw the rectangle.
Re: Recovering redacted information from pixelated videos
#57Earlier quoted context omitted.
Yes, I've also always felt there must be ways to extract more data from a moving clip, precisely because of the effect he explains, but then it seems that just superimposing the images doesn't actually extract that information, at least not all of it. But I wonder how to actually do it, do you have concrete ideas for a simple algorithm?
If you can figure out, for each frame, which sets of (pre-aligned) pixels have been averaged, you can create a large system of equations that captures those relations and solve it to find the unblurred pixel values. Depending on camera movement (and whether you might get "ground truth" information from pixels entering and leaving the areas near the borders) the system will be more or less well-conditioned. I'm going…
There are some (fairly old) papers that might contain some useful ideas for you:
- http://www.eyetap.org/papers/docs/mann94virtual.pdf - http://wearcam.org/orbits/index.html
I seem to recall that there used to be a video showing this approach in action. As input it took a video panning across a shelf full of books where the resolution was so low that the titles were illegible. And as output it produced a video with higher resolution and all the titles easily readable. Unfortunately I can't find that video any longer.
Re: Recovering redacted information from pixelated videos
#58So much brain power only to be used to de-blur japanese p0rn
Hah, I know you're joking here but this is (was) a thing: https://www.reddit.com/r/programming/comments/9sc0qj/deepcre...
It's actually mentioned in the original article:
> Side note: The potentially most extensive research on the problem of programmatically unblurring mosaic'ed regions from videos was done by Japanese Adult Video enthusiasts. Javplayer automatically detects blurred regions and performs upscaling via TecoGAN, and another person spent months improving their custom GAN that was trained with leaked videos (search for "De-Mosaic JAV with AI, Deep Learning and Adversarial Networks").
Re: Recovering redacted information from pixelated videos
#59Funny how the whole article talks about this approach, and then at the end shows the approach failing in the real world. I don't know about you, but I can't conclusively come up with a license plate in that final video.
Sure, but the technique used was also very trivial. Just aligning and averaging all the video frames basically leaves a mosaic-pixel-sized blur on everything (assuming the camera movement is uncorrelated with the mosaic grid). You can get much further by applying deconvolutions and using more math. I've been meaning to put some time into this myself but never got it off the ground. I wonder if the author would be ope…
> I wonder if the author would be open to making e.g. the car data available?
Interesting - this is same incorrect use of e.g. that the author made in a couple of places. Contrary to (apparently popular) belief, "i.e." and "e.g." can't simply be used as direct replacements for their English equivalents.
"e.g." is used to introduce one or more examples that satisfy a previously provided general form, for example:
I prefer fruit, e.g. apples or pears, over vegetables. Apples and pears being examples of fruit, not that an example is needed in this case, but for the sake of simplicity.
In the former example, "the car data" is not an example of "making".
"i.e." follows a similar rule. If there are exceptions for either, I'd be interested to know of them.
Re: Recovering redacted information from pixelated videos
#60Earlier quoted context omitted.
Not off the shelf but here are some tools. I have no experience with them. Wolf binarization - I think it makes the text more clear before OCR. https://github.com/chriswolfvision/local_adaptive_binarizati... This thing OCRs the pdf using Tesseract OCR https://github.com/ocrmypdf/OCRmyPDF/ Two other pdf tools https://github.com/qpdf/qpdf https://github.com/pikepdf/pikepdf
I'll play with the Wolf filter, thanks. Math typesetting is too messy for current OCR tools. It would be nice to reverse-engineer the LaTeX source for a math paper, but not likely soon. OCR for the language would help in mind-mapping a web connecting my saved papers, but I wouldn't use it for reading. I want everything to look like a 600dpi scan mixed down, as I would make, rather than what the libraries thought woul…
Found these 2 for math LaTeX OCR:
https://github.com/lukas-blecher/LaTeX-OCR
https://github.com/harvardnlp/im2markup
Also some LaTeX editors:
LyX https://en.wikipedia.org/wiki/LyX
TeXstudio https://en.wikipedia.org/wiki/TeXstudio
GNU TeXmacs https://en.wikipedia.org/wiki/GNU_TeXmacs