
Ask HN: Current methods/libraries for implementing handwriting OCR? - ChrisDutrow
What are some current methods for implementing OCR on handwriting?<p>This is what I have so far:<p>* Pre-process with some image filters, try combinations of: Black and white, Greyscale, edge detection(Canny?), line detection(Hough?)<p>* Try kNN (k nearest neighbor) algorithm first. This should be fast and work on easy stuff, but its more of a math equation and not really deep learning.<p>* Try a CNN (convolutional neural network). Probably use either the Keras or mxnet libraries<p>STILL tripping me up:<p>* Is there another machine learning technique I should try to apply to this other than the kNN and CNN strategies??<p>* Are there libraries that are more specifically geared towards handwriting OCR than Keras or mxnet? RNNLIB (too old?), ocropy?<p>* Lastly, I haven&#x27;t come across many methods to isolate characters and words from an image full of handwritten text. Figured I&#x27;d try to pull characters out and send them through the kNN algorithm, and pull characters and words out before putting them through the CNN engine.
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nkkollaw
I've tried a few OCR solutions. Ultimately, the best was Google Vision, by a
long shot.

It works great with unusual fonts/handwritten allcaps, and it's the absolute
best when it comes to working with low-resolution images.

I have no experience using it with hard-to-read handwriting, but it might be
worth checking it out if you don't know it already.

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ChrisDutrow
I just checked out google vision and it is the only online demo I was able to
get to read handwritten text. Had maybe a 60-70% success rate for poorly
written handwriting. And more like 85%-90% with good handwriting. Really cool.

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nkkollaw
Yes, it's really awesome.

Pretty cheap, too.

