Comment by xigency | Hacker News Reader

Comment by xigency | Hacker News Reader

To anyone screen capturing small fonts as a demonstration, or capturing digital text especially at a small resolution, I don't believe that that is the purpose of this OCR library. (As a specialized problem, that might be easier to solve depending on the typeface.)

A much better example that works quite well is a picture of someone holding a book: http://i.imgur.com/3JWs64x.jpg

    Magic .
    Read this to yourself. Read it silently
    Don't move your lips. Don’t make a suund
    Listen to yourself. Listen without hearing
    What a wonderfully weird thing, huh?
    NOW MAKE THIS PART LOUD!
    SCREAM IT IN YOUR MIND!
    DROWN EVERYTHING OUT.
    Now, hear a whisper. A tiny whisper.
    New, read this next line with your best crotchety—
    old-man voice:

    “Hello there, sonny. Does your town have apost 0
    Awesome! Who was that? Whose voice was that?
    It sure wasn’t yours!

    How do you do that?
    How?!
    Must be magic.

Problems with this text: misspelled 'sound' as 'suund', didn't recognize the word 'anything', and mis-recognized 'a post office' as 'apost 0'.

Not bad. Especially since two of three mistakes are on the edge of the page.

The old man voice was spoken in my mind as Deckard Cain.

I stayed a while and I listened

it was instantaneous Deckard Cain for me.

Isn't this an issue with the algorithm?

Can someone try and see how it would perform if you simply upscale the image using normal bicubic interpolation? And if it performs much better, I feel like that should be a preprocessing option to scale up the image since it seems to do so poorly on small resolutions.

Tesseract's Github Readme actually recommends upscaling for better results:

https://github.com/naptha/tesseract.js#tesseractrecognizeima...

> Note: image should be be sufficiently high resolution. Often, the same image will get much better results if you upscale it before calling recognize.

Presumably, the result would be even better if you put a filter that did a path-tracing/auto-vectorization step first, upscaled by an arbitrary amount, and then rasterized the result. Analogue sources would have their traced paths distorted by such a process in a way that's lossier than just using the noisy analogue source—but for actually-digital-from-the-beginning images, it'd work perfectly.

This would be really cool! We would welcome a pull request and / or link to any downstream project working on this. In a similar vein, we've been considering adding the stroke width transform [0] as an optional preprocessing step.

[0] https://www.microsoft.com/en-us/research/publication/stroke-...

Thanks, the text is awesome!

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