Re:When you browse Instagram and find Tony Abbott's passport...
by jacquesm on Wednesday September 16, 2020 @07:09AM
(#24491449)
Interesting, thank you for the link. I had a hunch this should be possible but I wasn't aware that it was already proven. I used a similar trick on image recognition: turn images into a single 32 bit word by heavy pixelation and then look up a matching description. It's interesting how often that will work once you feed it with enough data. After all, that gives you 4 billion inputs mapped onto 4 billion descriptions, and plenty of those will contain the Eiffel tower with various cloudy backgrounds apparently recognized perfectly.
It's a total cheat but it is funny how close that can get you to something that might be actually useful.
Re:When you browse Instagram and find Tony Abbott's passport...
by Jugurtha on Wednesday September 16, 2020 @07:49AM
(#24491682)
I wonder if you could use adaptive optimal kernels, AOK[0]? I had used this for work on multiphase flow recognition from an electrical capacitance tomography, ECT, as a proxy for void fraction. We wanted to tinker with time-frequency representations.
[0]: https://pdfs.semanticscholar.org/20c2/b82eef0809df80a402f125...
Re:When you browse Instagram and find Tony Abbott's passport...
by jacquesm on Wednesday September 16, 2020 @10:16AM
(#24492900)
> electrical capacitance tomography
Mind blown. Wow, that is very impressive.
Re:When you browse Instagram and find Tony Abbott's passport...
by Jugurtha on Wednesday September 16, 2020 @08:20PM
(#24499717)
Yes, that is cool. I had just come back from an internship in Wireline at Schlumberger where I was exposed to tools like one that did nuclear magnetic resonance, NMR, thousands of metres below. Pretty sweet tech. Transitioned to ECT for that project, then ECG for anomaly detection on anonymized hospital patient data. I never will underestimate the effect hair and sweat have on data. That was a cool year with lessons that served well later.
You can dictionary attack pixelated photos.
With Gaussian kernels, besides deconvolution you can sometimes also dictionary attack them if you have the original font and if the kernel is properly normalized kernel (i.e. most gaussian blurs).
Although I haven't tried, I think there may even be neural network based techniques that can perform even more effectively than a dictionary attack.
Separately, if the image editing tools added sufficient random noise to their mosaic filters they might be able to thwart most of these attacks, or at least make them significantly harder.