Re: Graphic to Text Interpretation

Hi scsu_13!

There are a lot of documentation about

OCR (optical character recognition) on the web. However, most of them are all about maths and maybe a bit harder for an average level (like mine

)

According the reduced number of glyphs you have to decode (9), their location (in cell center), their orientation (horizontally aligned), a simpler approach may interest you:

Bayesian theorem (or

fuzzy logic)

The principle is to obtain a (enough high) probability that your glyph is (let's say) rather a '5' than a '9'.

The

Bayesian theorem can tell how

probable is an event in a context, according previous statistics done on this event in same context.

It is used for instance in photography where camera should recognize the type of photography (portrait or landscape or macro). Given statistics (metrics on focal, light distribution, contrast, etc) of hundred of landscape portrait and macro pictures, the camera feeds the Bayesian algorithm with current metrics and obtain the most probable type of current photo. The beauty of this algorithm is how silly it is (a 'landscape' means nothing for it) and how accurate are its predictions.

The same algorithm is used in anti spam software. They too do not understand the email content but can predict (and learn from user) what is a spam.

I hope this can inspire you:

You may get some metrics on values scanned for a suduku cell (let's say array of 12x12 spots with values from 0 to 255), like average value, symmetry, gravity center, etc, and use the results to find the most probable value.

ie: if there is an vertical symmetry, its probably '0' or '8'.

or if most of dots are on the right, its probably a 3 or 9

etc...

Anyway you have a very interesting challenge

Keep us inform of your solution (and problems

).

Best regards

Miki.

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