To let you know,
can't see images yet...


On Thu, Apr 7, 2011 at 8:17 AM, Amrit <[email protected]> wrote:
> Hi Dmitri/Partik,
> Thanks for your reply.I am sending along the pre processed test image which
> I had mentioned in my response.
> tesseract output - SOUTHBURY~ CT DLUBB
>
> Regards,
> Amrit.
>
> On Wed, Apr 6, 2011 at 12:05 AM, Dmitri Silaev <[email protected]>
> wrote:
>>
>> Agree not to use dictionary at all. IMO the best you can do is:
>> - use appropriate whitelists for each character position
>> - obtain a set of char choices for every char position
>> - restrict choice sets by using other semantic information you may have
>>
>> Warm regards,
>> Dmitri Silaev
>>
>>
>>
>>
>>
>> On Wed, Apr 6, 2011 at 6:00 AM, Amrit <[email protected]> wrote:
>> > 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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>> >
>
>

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