Please send some information if you successfully get through it. I am 
working on the same issue on Android.



W dniu czwartek, 8 grudnia 2016 19:20:06 UTC+1 użytkownik Marie napisał:
>
> Got it. Thanks a lot!
>
> On Thursday, December 8, 2016 at 12:50:23 AM UTC-8, Ashish Goel wrote:
>>
>> It depends. Extent of automation will depend upon your images.
>> If all of your images are same in size, then you can find coordinates of 
>> your sections (Like header, store address, billing info) and use a tool 
>> (for ex. imagemagick) to crop all of your images. Do OCR and then see what 
>> needs to be looked at.
>>
>> if your images are of different sizes that you may have to do some kind 
>> of image processing to rescale, resize and many other things, which will 
>> gain depend upon the variations.
>>
>> On Thursday, December 8, 2016 at 1:13:14 PM UTC+5:30, Marie wrote:
>>>
>>> Thank you Ashish for the suggestion. 
>>>
>>> The challenge is how to automate this process, any thoughts?
>>>
>>>
>>> On Wednesday, December 7, 2016 at 1:00:59 AM UTC-8, Ashish Goel wrote:
>>>
>>>> Crop image into sub images and then OCR. Crop it in different segments.
>>>>
>>>> On Saturday, December 3, 2016 at 5:54:51 PM UTC+5:30, Marie wrote:
>>>>>
>>>>> Hi,
>>>>>
>>>>> We are trying to recognize receipt using Tesseract (v3.02 on 
>>>>> Windows). Tried to process the images but the words accuracy (comparing 
>>>>> with OneNote's result) is still not good. 
>>>>>
>>>>> Any suggestions on how to improve accuracy?
>>>>>
>>>>>
>>>>> p.s.attaching the raw image, processed image with OCR results by 
>>>>> Tesseract,
>>>>>
>>>>> raw image:
>>>>>
>>>>>     
>>>>>
>>>>> text recognized from raw image:
>>>>>
>>>>>
>>>>>  
>>>>>
>>>>>
>>>>> processed image (scaled 200%, increased contrast, cropped border)
>>>>>
>>>>> Thanks,
>>>>> Marie
>>>>>
>>>>>

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