*Thanks for all the help.*
*I tried closing as a morphological transformation and also used a
threshold to get a black and white picture.*
*I got "BYC3 .- A4UFYY.QLBGY -+ " as a answer this is almost right.*
*Is there anything else that i can do to improve the detection?*
*i attached the python code that i used and the picture after
the preprocessing.*
import cv2
import pytesseract
import numpy as np
from scipy import ndimage
img = cv2.imread('voucher.png')
img = cv2.bitwise_not(img)
img = cv2.resize(img, None, fx=2, fy=2, interpolation=cv2.INTER_CUBIC)
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
_,img = cv2.threshold(img,145,255,cv2.THRESH_BINARY)
kernel = np.ones((2, 2), np.uint8)
img = cv2.dilate(img, kernel, iterations=1)
img = cv2.erode(img, kernel, iterations=1)
img = ndimage.rotate(img, -20)
cv2.imwrite("changed.png",img)
pytesseract.pytesseract.tesseract_cmd = r'C:\Program
Files\Tesseract-OCR\tesseract.exe'
print(pytesseract.image_to_string(img))
nikhilf...@gmail.com schrieb am Dienstag, 1. November 2022 um 04:59:55
UTC+1:
> Hi,
>
> Combination of image deskewing and image inversion should work.
>
> Use PSM 11 on processed image, it will detect most of the characters.
>
> Thanks,
> Nikhil
>
> On Tue, Nov 1, 2022, 6:16 AM kwmz...@gmail.com <kwmz...@gmail.com> wrote:
>
>> So I think you could also try using some morphological transformation; I
>> feel like dilation could help a lot too
>>
>> On Monday, October 31, 2022 at 2:01:36 PM UTC-4 nabil-ak wrote:
>>
>>> https://imagetotext.info/
>>>
>>> If i use a website like this one it can extract the text perfectly and
>>> they also use tesseract.
>>> There has to be some preproccesing/setting that makes tesseract detect
>>> the text perfectly.
>>>
>>> nabil-ak schrieb am Montag, 31. Oktober 2022 um 13:55:56 UTC+1:
>>>
>>>> *I also tried Rotation but its still not working.*
>>>>
>>>> *These are the preprocessing steps that i used:*
>>>>
>>>> import cv2
>>>> import pytesseract
>>>> import numpy as np
>>>> from scipy import ndimage
>>>>
>>>> img = cv2.imread('voucher.png')
>>>>
>>>> img = cv2.bitwise_not(img)
>>>>
>>>> img = cv2.resize(img, None, fx=1.2, fy=1.2, interpolation
>>>> =cv2.INTER_CUBIC)
>>>>
>>>> img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
>>>>
>>>> kernel = np.ones((1, 1), np.uint8)
>>>> img = cv2.dilate(img, kernel, iterations=1)
>>>> img = cv2.erode(img, kernel, iterations=1)
>>>>
>>>> img = ndimage.rotate(img, -20)
>>>>
>>>> cv2.imwrite("changed.png",img)
>>>>
>>>> pytesseract.pytesseract.tesseract_cmd = r'C:\Program
>>>> Files\Tesseract-OCR\tesseract.exe'
>>>> print(pytesseract.image_to_string(img))
>>>>
>>>>
>>>> abey...@gmail.com schrieb am Montag, 31. Oktober 2022 um 10:46:59
>>>> UTC+1:
>>>>
>>>>> Did you try all the preprocessing steps? Rotation / Deskewing ? I
>>>>> think Tesseract finds it difficult to identify skewed images.
>>>>>
>>>>> On Mon, Oct 31, 2022 at 1:17 PM nabil-ak <akir...@gmail.com> wrote:
>>>>>
>>>>>> Hello,
>>>>>>
>>>>>> I want to detect a code (combination of characters) on an image in
>>>>>> python.
>>>>>>
>>>>>> I already tried EasyOCR <https://github.com/JaidedAI/EasyOCR> and
>>>>>> Tesseract
>>>>>> Open Source OCR Engine <https://github.com/tesseract-ocr/tesseract> but
>>>>>> noone could detect the characters.
>>>>>>
>>>>>> I also tried to preprocess the picture by inverting the white font to
>>>>>> a black font and painting the background white to make it for the engine
>>>>>> easier to detect the characters.
>>>>>>
>>>>>> *What am i doing wrong?*
>>>>>>
>>>>>>
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>>>>>> To view this discussion on the web visit
>>>>>> https://groups.google.com/d/msgid/tesseract-ocr/2e764275-4992-495f-b0ac-ffe668254231n%40googlegroups.com
>>>>>>
>>>>>> <https://groups.google.com/d/msgid/tesseract-ocr/2e764275-4992-495f-b0ac-ffe668254231n%40googlegroups.com?utm_medium=email&utm_source=footer>
>>>>>> .
>>>>>>
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