Please see
https://code.google.com/p/tesseract-ocr/source/browse/training/degradeimage.h
https://code.google.com/p/tesseract-ocr/source/browse/training/degradeimage.cpp

It maybe possible to do additional training using degraded versions of
'synthetic' images which may improve recognition of older documents.

ShreeDevi
____________________________________________________________
भजन - कीर्तन - आरती @ http://bhajans.ramparivar.com

On Thu, Apr 2, 2015 at 7:05 PM, Sven Pedersen <[email protected]>
wrote:

> Cool! Good work. I hope that will help the others who have been asking
> about Georgian for a couple years. :-)
> --Sven
>
> On Wed, Apr 1, 2015 at 9:28 PM, Derek <[email protected]> wrote:
>
>> I've recently finished training tesseract 3.03-rc1 on the Georgian
>> language, using tesstrain.sh and based off the files in the langdata
>> repository. I created my own word list and bigrams list using Wikipedia.
>>
>> Performance is very good on high-quality scans with modern fonts, but it
>> doesn't do very well on older documents; I'm not sure whether this is
>> because of differences in the font, or because the synthetic images
>> generated by the tesstrain.sh script don't give tesseract enough training
>> in handling degraded images.
>>
>> I've uploaded the traineddata file and all training files here:
>> https://dl.dropboxusercontent.com/u/11840441/kat_train20150401.zip
>>
>> I'm attaching a test image (a randomly-selected scan from Georgia's
>> registry of corporations) and the output of running tesseract recognition
>> on the test image. No pre-processing was done on the test image except to
>> upsample it to 300dpi. The test image contains some Latin characters so I
>> ran tesseract with the language selector "kat+eng".
>>
>> The licensing for any documents to which I hold the copyright is the same
>> as the tesseract source, i.e. the Apache License, Version 2.0 (
>> http://www.apache.org/licenses/LICENSE-2.0).
>>
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>
>
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