this post was submitted on 20 Aug 2023
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Memes

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[–] [email protected] 15 points 10 months ago (1 children)

I would assume, you have a standard text. That you handwrite. Then scan, so that the 3d printer can write in your handwriting!

All that for nobody to be able to read my crappy handwriting ;)

[–] [email protected] 10 points 10 months ago* (last edited 10 months ago) (1 children)

Its much more difficult than that to be actually believable. As u/Luftruessel said, theres a great video from “Stuff Made Here” where he goes deep inside the topic and tries to fool a graphologist.

[–] [email protected] 9 points 10 months ago (1 children)

Yeah you'd need a dozen or so examples of each character for randomness and the professor who can see the shenanigans would just ask for a paper in cursive.

[–] [email protected] 4 points 10 months ago (1 children)

But the letter shapes change slightly depending on what letters are before and after.

[–] [email protected] 3 points 10 months ago (2 children)

You don't just scan individual letters, you also scan a bunch of different combos of letters next to each other, as needed. For example, you're gonna want specific scans for things like "ea","ee", "eu".

[–] [email protected] 2 points 10 months ago (1 children)

Getting several examples of every letter combination gets very hard very fast. Just lowercase, to get 5 examples of the letters before and after each letter is nearly 100k examples. You'd probably be better off doing some machine leaning shenanigans to simplify the process from training data.

[–] [email protected] 3 points 10 months ago* (last edited 10 months ago)

I didn't say every letter combination. I said the ones you need. Letter combos that do not connect to each other aren't needed. Still though, you're right that machine learning is needed... the good news is it's already been done before, and the code is open source. StuffMadeHere on youtube already built a fully functional prototype that impressed if maybe didn't fool forgery experts. https://youtu.be/cQO2XTP7QDw

[–] [email protected] 1 points 10 months ago

Please watch the video