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Google Docs' OCR Quality Tested
orenh writes "Google has released a Google Docs application for Android, which includes the ability to create documents by OCR-ing photos. I tested the application's OCR quality and found that it's mediocre under the best conditions and poor under real-world conditions. However, I believe that this poor performance is caused in part by an intentional decision by Google."
There are a number of scanner apps in the market that do a much better job in the first step of this process, which is taking the picture. They then concentrate their efforts on producing a clean usable PDF of the document. I tested one of these and found that the PDF rendered by it was much better than the PDF produced by Google.
Everything is crisp and readable.
If the first fails, its no wonder the second OCR step fails.
Sig Battery depleted. Reverting to safe mode.
He uploaded the 120 dpi image instead of the 300 dpi image and is surprised the OCR sucks. Really? Lossy isn't the concern when you're OCR'ing bloack text on a white background. Seriously. Think about what the image is actually going to be used for, then make your decision.
And, seriously, how effective of OCR'ing are you really imagining you're going to get off of a camera phone pic, anyway?
If brevity is the soul of wit, then how does one explain Twitter?
If the increasing absurdity of the CAPTCHAs I tend to see is anything to go by, there are programs out there that'll read normal printed text from even the crappiest photo without missing a beat. The question is, are the spammers using standard commercial solutions, or have they got some useful tech of their own that we might be able to get our hands on (seize it as part of a settlement and make it public domain, for instance).
Google took the Tesseract OCR engine, one of the first engines, and wrapped document analysis and some high level improvements on it. In the current OCR market landscape there are only 4 commercial engines, and two that make up 98% of the market. Compared to those two OCROpus is not even close because of the legacy engine. So the real reason is it's old technology, very old. Unless Google licenses ABBYY or Nuance they will not get any better. The reality is OCR takes 50 man-years to develop to compete with these top two engines, and it's just not practical for even Google to go out and start from scratch.
I don't think that spammers have any amazing tech, they just have different requirements. They can still send spam with a 1% success rate whereas with OCR you'd want a 99% success rate.
I once worked on an OCR project. The client specified a 99% success rate and we strained to restrain our grins. 99% is about one error every one or two lines of text. We got 99.6% in our first implementation before we even began to work on accuracy. Admittedly we had excellent image quality. This was a custom solution that had its own optics.
Does that mean it couldn't be a viable candidate for some Summer of Code work then?
More like a bunch of masters/phd thesis to get started.
OCR is an area of AI research under the topic of Computer Vision. It is yet another area that seems simple in concept but turns out to be incredibly difficult in practice.