Tesseract 2.04 does pretty well for accuracy -- at worst, I get the
occasional full-stop turning into a hyphen/dash. All pretty simple to
fix. Problem is, Tess2.04 can't handle double-quotes -- instead it dies
with this error:
philpem@cheetah:~/$ tesseract elek0002.tif elek0002_tess2
Tesseract Open Source OCR Engine
tesseract: unicharset.cpp:76: const UNICHAR_ID
UNICHARSET::unichar_to_id(const char*, int) const: Assertion
`ids.contains(unichar_repr, length)' failed.
Aborted
If I use Tesseract 3 (the current SVN release), then I can OCR the page:
philpem@cheetah:~/$ LD_LIBRARY_PATH=/tmp/tess/lib
/tmp/tess/bin/tesseract elek0002.tif elek0002_tess3
Tesseract Open Source OCR Engine with LibTiff
But the error rate is FAR worse. The page numbers on the right-hand side
of the page are completely gone, the first line is mush (random letters)
and upper-case "M" gets OCR'd as "l\/l" (usually when the page contains
a frequency, e.g. "89 MHz").
The assertion failure seems to be a manifestation of Issue #265
(http://code.google.com/p/tesseract-ocr/issues/detail?id=265), which is
apparently "fixed in Tesseract 3". What I'd like is the recognition
accuracy of 2.04, with the stability of 3.0 (or at least the bugfix for
#265)...
Is there any way to get the accuracy back where it was with 2.04 (or at
least get the page numbers back)?
I've uploaded my test images here:
http://www.philpem.me.uk/temp/tesseract/
Both are greyscale TIFFs.
ELEK0001.TIF is a "works fine" example that OCRs almost perfectly in
Tess2.04 but has significant errors in Tess3.0-svn.
ELEK0002.TIF crashes Tess2.04, works in Tess3.0-svn, but has a lot of
errors (especially on the first line).
When processed with Tess3.0, the page numbers (right-hand column) are
omitted from the output .TXT file.
Thanks,
Phil.
There is mention in one of the Tesseract papers that the training data
was extended on thousands of pages from Google Books, but whether or
not that's what's actually in the language packs... who knows?
> In any case, I routinely come accross certain pages
> where recognition is terrible and where there is no doubt that the
> cause is a missing font.
--
<Leftmost> jimregan, that's because deep inside you, you are evil.
<Leftmost> Also not-so-deep inside you.