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Comment by ToothlessJake | Hacker News Reader

Thats OCR...

Well, it doesn't go all the way, at least in this implementation (contrary to Xerox's statement, we've been told compression is not standardized), to actually recognize the symbols it finds. If it did, it would presumably make many fewer of these errors, maybe almost none since when it's uncertain it could just go with the original.

O-SubC-R then perhaps. Still is recognizing shapes/symbols which is the very basis of OCR.

This seems a bit hair splitty when the end result is the same as invalid OCR dictionaries.

Well sure, but then why don't we just call it "lossy GZIP"? OCR is a pretty specific subset, and produces characters - this does not produce computer-readable characters, therefore not OCR.

What are you on about? What does it produce if not computer-readable characters? Computer illegible characters? Are you saying it cannot read from the dictionary it creates? Or from the characters it is later optically recognizing off that dictionary?

Again from the JBIG2 wiki[1]:

"Textual regions are compressed as follows: the foreground pixels in the regions are grouped into symbols. A dictionary of symbols is then created and encoded.."

It seems not only is JBIG2 being deployed as OCR by Xerox for whatever reason, its implementation in this case is an absolute failure.

[1] http://en.wikipedia.org/wiki/JBIG2

Does it produce ASCII? UTF? If no, it's not OCR.

edit: by the definition you seem to be going on, any facial recognition is also OCR, since you could consider a face a 'glyph' (edit: 'symbol'). The only 'text' thing here that I can see is that it is intended to be used on text, which lends some optimizations, nothing that it's actually text-based in any way.

If you make a font out of faces and use them as repeated glyphs then yes it's OCR. If you're not using identical symbols over and over than I don't think you have a sane definition of 'glyph'.

OCR per definition gives out text. Not binary data that resemble the bitmap of the input image.

It produces symbols, not characters.

Say that the scanner internally splits the scan into regions of 10x10 pixels that it saves in memory. If another region differs on less than (say) 10% of the pixels it is assumed that the two zones are identical and the first one is used in the second place too. The regions have no semantic meaning.

OCR translates the scan into a character set.

The only thing that's missing is a mapping from 'symbol #28' into 'ascii #63'. Internally it's storing instances of symbols plus font data for those symbols.

Also, something to think about: an EBCDIC document accidentally printed as ASCII/8859-1 would have equally zero semantic meaning when fed into an OCR program. But I don't think anyone would argue it wasn't OCR.

That "only thing that's missing" is a very very big thing, and difficult to get correct. And where does it say it's storing font data for the symbols?

A font doesn't need to be anything more than a series of bitmaps. And then each character location on the image, ignoring errors, references one of these bitmaps. That's how documents with embedded bitmap fonts generally work.

That mapping isn't a very big thing. Sometimes text-based PDFs don't even have it, and you don't notice unless you try to copy out and get the wrong letters.

OK down-voter. Read the JBIG2 wiki[1].

"Textual regions are compressed as follows: the foreground pixels in the regions are grouped into symbols. A dictionary of symbols is then created and encoded, typically also using context-dependent arithmetic coding, and the regions are encoded by describing which symbols appear where."

Then from the OCR wiki[2].

"Matrix matching involves comparing an image to a stored glyph on a pixel-by-pixel basis; it is also known as "pattern matching" or "pattern recognition"."

Furrow your brow and smash the down-vote arrow all you wish. It won't stop JBIG2 from doing much of what people consider OCR as doing today. Recognizing characters, just JBIG2 adds in making it's own dictionary which opened the path to this topic today.

[1] http://en.wikipedia.org/wiki/JBIG2 [2] http://en.wikipedia.org/wiki/Optical_character_recognition

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