Stefan,

I figured this out long ago as part of an font-independent OCR design
project. An initial pass over all interesting patterns constructed a
decision tree, where a group of key pixels was examined, which then led to
which was the next group of pixels to examine, etc. The initial pass sorted
things out as to balance the prospects of each group to as near 50:50 as
possible. Each leaf on the decision tree corresponded to identifying a
particular character. The groups of pixels tended to be arranged in line
segments to see if structures in particular parts of a character crossed
the line segment.

Of course this approach made presumptions regarding the nature of images,
e.g. that pixels were either black or white. Your presumptions would be
different, so your method would be different. The key here is to figure out
what your identifying prototypes would look like, and then look at what it
takes to both create and to use them.

*Steve Richfield*

On Sun, Aug 8, 2021 at 9:20 AM stefan.reich.maker.of.eye via AGI <
[email protected]> wrote:

> I'm dreaming up the ultimate image recognizer. Turn on webcam, let learn.
> After a minute, check the results and give names to stuff. The software
> will have found out what a face is (roughly), but of course not what the
> word for "face" is.
>
> https://botcompany.de/images/1102998
>
> PS: Discord <https://discord.gg/kcKKZEg>
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