Hi All,
I am trying to evaluate tesseract to decode US postal address
from a set of images(english text with varying font).I want to extract
the city,state zipcode combination from the image.In doing so, out of
the box tesseract 3.01 performance is average and I would like to
increase the accuracy of the system by providing a custom grammar/
wordlist (language model).
Any idea as to how to accomplish this?(My custom grammar/
language model will only contain City,State and ZipCode numbers).
I have tried to create custom dawg by following on the lines of
'training tesseract 3' wiki page, but this doesn't seem to work at
all.Is there any way I can do this without training a subset of my
test images?
Regards,
Amrit.
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