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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.

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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-...

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