如何在小图像中使用 pytesseract 改进手写文本识别？

Question

I want to do handwritten text recognition using the pytesseract library to read a numerical character in images that has an average dimension of 43 * 45 pixels. The following sample image:

expected result:

9
1
4

I want to get a single numerical character from the image.

I've tried this code below

import pytesseract

# loop through images
print(pytesseract.image_to_string("text.jpg", config='--psm 10 --oem 3 -c tessedit_char_whitelist=0123456789'))

but the real result, I got less than 50% of accuracy or even much lower, some numbers that read well, some that read 2 characters in a single image, some that didn't read.
When I remove the -c tessedit_char_whitelist = 0123456789 configuration, I get the characters 4 , \ , and the letter g .
How to make Pytesseract treat images as an only single numerical character instead of using a whitelist that still reads the text as alphanumeric ?

PS: I know that OCR is can't 100% accurate. At least the accuracy can be improved.

Answer 1

Accordingly to this GitHub issue , tesseract 4.0 does not support whitelist characters with the LSTM model. You can fix this issue by upgrading Tesseract to the 4.1 version instead of using the legacy model (ie, --oem flag).

Alternatively, you could try to use the flag config='digits' as proposed by Robert Harris in this answer to force your pytesseract into returning only digits.

This blog article proposes the creation of a python function that uses a simple regex to extract all numbers instead of juggling around with several flags and versions.