On Mar 31, 6:48 am, Leith Bade <[email protected]> wrote:
> Hi,
>
> I am working on a image processing assignment and I would like to use
> Tesseract for recognising the letters/numbers on the plate after it
> has been located.
>
> I want to use Tesseract as OCR is hard and this library claims that it
> can handle skewed and curved lines.
>
> I seems to work reasonably well but I think I need to tweak the
> settings.
>
> So far I have told it to only look for A-Z and 0-9.
>
> It seems to try to break the number plate up into words, when it
> should be a single 'word'.
>
> It also tries to stick words into all numbers or all letters rather
> than letting it mix. e.g. 4536B becomes 45368.
>
> So how do I get it to disable the word breaking, and disable the
> dictionary/number classifier part.
>
> Is it possible to tell it some sort of pattern to match? All the
> number plates I need to recognise follow these patterns:
> S[C or D][A to Z]xxxx[A to Z]
> S[C or D][A to Z]xxx[A to Z]
> S[C or D][A to Z]xx[A to Z]
> EA to Z]xxxx[A to Z]
>
> Some of the S... number plates are split into two lines:
>
> S[C or D][A to Z]
> xxxx[A to Z]
>
> S[C or D][A to Z]
> xxx[A to Z]
>
> x = [0 to 9]
>
> Thanks,
> Leith

hi, Leith,

I believe the real challenge to apply ocr for plate recognition is
that the plate image are "too dirty" comparing to paper documents.
There are frames, skews, un-even shadows, etc. You have to do your own
work to parse the plate into separate chars and feed the ocr engine. I
don't think tesseract itself can handle this automatically given the
raw image. But I believe it will do pretty well once you get the
binarized separate chars. Basically, plate recognition is more a image
processing problem than ocr problem.

You can use the grammar as post-process to make corrections. That's my
2cents.

zl2k

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