Post-process and read blurred digits - OpenCV / tesseract

Question

My boss just gave me 9000 images showing a multi-meter output, and he wants me to read them all and write the voltage output on a text file for Monday morning!

There's no way I can do it manually , so I desperately need your help to automate the process.

I have already done a bit of coding. The multimeter screen position is fixed over the 9000 images, so I just cropped the pictures and zoomed on the screen.

Here's my code so far :

import pytesseract as tess
tess.pytesseract.tesseract_cmd = r'D:\Programs\Tesseract-OCR\tesseract.exe'
from PIL import Image
from matplotlib import pyplot as plt
import cv2
import numpy as np

img = cv2.imread('test1.png')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (7,7), 0)
ret, BW = cv2.threshold(gray, 0, 255, cv2.THRESH_OTSU + cv2.THRESH_BINARY)

plt.imshow(BW)
plt.show()

print(tess.image_to_string(img,config='digits --oem 3'))

My code outputs this kind of picture:

For this picture, tesseract reads the following number: 138

I have two problems here: the first one is I don't know how to properly pre-process my pictures for tesseract to easily read them.

Second problem: I don't know how to process the decimal dot. In fact, on some picture there is no decimal dot, so I need to find a way to make tesseract read it.

Do you think I'll need to manually "train" tesseract, so that I reach a near 100% accuracy?

Thank you sooo much for your help, I'll continue my research meanwhile on the OpenCv functions!

here's one of the originals:

UPDATED VERSION:

Ok so I updated a bit my code so far :

# Loading the picture
img = cv2.imread('test1.JPG')

# Crop - Rotate - Scale up
x = 1400
y = 1375
h = 325
w = 800
img = img[y:y+h, x:x+w]
image = cv2.rotate(img, cv2.ROTATE_180)

gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

thresh = cv2.threshold(gray, 128, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5,10))
close = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel, iterations=1)

cv2.imshow('close', close)

x = 0
y = 0
h = 300
w = 750
img = close[y:y+h, x:x+w]

plt.imshow(img)
plt.show()

print(tess.image_to_string(img,config='--psm 7 -c tessedit_char_whitelist=0123456789 --oem 0'))

I get a finer image for tesseract to analyse. But still no luck with the decimal dot :/.

Answer 1

you need around 3-4 hours to type them manually, just spend 1 extrahour to write a wrapper that opens the image and let's you input a value.

when automating, my biggest concern would be if all the measurements have the same unit of kilo-ohm, you should really include that check in your open-cv code.

good luck!