thank you all.

Lorenzo Bolzani <[email protected]> 于2019年3月8日周五 下午5:06写道:

>
> I someone wants to try this and is looking for a python implementation
> here is one:
>
>
> http://scikit-image.org/docs/dev/auto_examples/segmentation/plot_niblack_sauvola.html
>
> https://github.com/scikit-image/scikit-image/pull/905/files/bb6af8ec723776fc821654847aec04a652f70042
>
>    binary_phansalkar = threshold_sauvola(image, w=25, method='phansalkar',
> r=50)
>
>
> (I did not try it yet)
>
>
>
> Lorenzo
>
>
> Il giorno ven 8 mar 2019 alle ore 08:28 'Lars Fricke' via tesseract-ocr <
> [email protected]> ha scritto:
>
>> Hi,
>>
>> we use the local Phansalkar binarizer with default values. you can try
>> that very easy in the imagej fiji package. works perfect for all kinds of
>> input, especially with scans with poor lightning and bad contrast.
>>
>> there is a nice comparison and yet another method in
>>
>> https://www.google.com/url?sa=t&source=web&rct=j&url=https://arxiv.org/pdf/1609.08078&ved=2ahUKEwjasPKLgvLgAhXLJVAKHdrHCV8QFjAAegQIBRAB&usg=AOvVaw1VmuXsg5fEG3hTTkg_7WcZ
>>
>> regards lars
>>
>>
>> 易鑫 <[email protected]> schrieb am Mi., 20. Feb. 2019, 03:56:
>>
>>> Hello,everyone:
>>>    In the tesseract wiki   "
>>> https://github.com/tesseract-ocr/tesseract/wiki/ImproveQuality";, it
>>> says the importance of  binarisation to the final recognition result. I
>>> have tired many methods for choose a suitable threshold, but I have not
>>> find a very perfect method.
>>>    Does anyone have the experience on choose a suitable threshold for
>>> binarisation,please teach me,thanks a lot.
>>>
>>> Sorry for my poor english.
>>>
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