Thanks for the shout.<br>
<br>
I've got my current project in the box. Both "gocr" and "ocrad"
had me correcting 30-40 errors per page. Neither seemed to be
overly concerend with run-together words. Perhaps that is a
problem with how the dictionary is used by those programs. I ran
the ocr results through Open Office one more time and that seemd to
clean up most of the stuff.<br>
<br>
You'd never be able be able to use these programs to do automated forms
processing. It'd require too much operator intervention and
probably be just as easy to re-transcribe by hand. In a
production setting, I'd probably be able to justify the purchace of
well developed software ... just now, I'm only playing.<br>
<br>
Thanks again,<br>
<br>
Harv<br>
<br><br><div><span class="gmail_quote">On 10/24/05, <b class="gmail_sendername">Leif Johnson</b> <<a href="mailto:leif.t.johnson@gmail.com">leif.t.johnson@gmail.com</a>> wrote:</span><blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
<br>
<div><span class="q"><blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;"><br>
I've tried "gocr" and "ocrad" ... the results are less than
favorable. I'm looking for something with an error rate of
less than 10 per 1000 charaters. </blockquote></span><div>I
don't think you will find it. OCR that is this good is usually
doing target matching, which doesn't sound like it is an option for
you. What kind of error rate are you getting anyway? You
might just have to bite the bullet and do a little keying for low
confidence results....<br>
<br>
leif<br>
<br>
</div></div><br>
</blockquote></div><br>