I'm trying to extract text from image using python cv2. The result is pathetic and I can't figure out a way to improve my code. I believe the image needs to be processed before the extraction of text but not sure how.
I've tried to convert it into black and white but no luck.
import cv2
import os
import pytesseract
from PIL import Image
import time
pytesseract.pytesseract.tesseract_cmd='C:\\Program Files\\Tesseract-OCR\\tesseract.exe'
cam = cv2.VideoCapture(1,cv2.CAP_DSHOW)
cam.set(cv2.CAP_PROP_FRAME_WIDTH, 8000)
cam.set(cv2.CAP_PROP_FRAME_HEIGHT, 6000)
while True:
return_value,image = cam.read()
image=cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
image = image[127:219, 508:722]
#(thresh, image) = cv2.threshold(image, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
cv2.imwrite('test.jpg',image)
print('Text detected: {}'.format(pytesseract.image_to_string(Image.open('test.jpg'))))
time.sleep(2)
cam.release()
#os.system('del test.jpg')
Preprocessing to clean the image before performing text extraction can help. Here's a simple approach
First we convert to grayscale then sharpen the image using a sharpening kernel
Next we adaptive threshold to obtain a binary image
Now we perform morphological transformations to smooth the image
Finally we invert the image
import cv2
import numpy as np
image = cv2.imread('1.jpg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
sharpen_kernel = np.array([[-1,-1,-1], [-1,9,-1], [-1,-1,-1]])
sharpen = cv2.filter2D(gray, -1, sharpen_kernel)
thresh = cv2.threshold(sharpen, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3))
close = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel, iterations=1)
result = 255 - close
cv2.imshow('sharpen', sharpen)
cv2.imshow('thresh', thresh)
cv2.imshow('close', close)
cv2.imshow('result', result)
cv2.waitKey()