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.
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.
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.
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.
