I am trying to improve the accuracy of an OCR I wrote. It performs well for a normal image but struggles for a noisy image.
The noisy image:
I wrote a function to remove the noise and it does remove a lot of the noise present but also diminishes the text a bit. I am only able to capture around 60% of the text. I tried adjusting the contrast, sharpness and threshold but not able to improve OCR performance.
import cv2
import pytesseract
import numpy as np
def noise_remove(image):
kernel = np.ones((1,1), np.uint8)
image = cv2.dilate(image, kernel, iterations=1)
kernel = np.ones((1,1), np.uint8)
image = cv2.erode(image, kernel, iterations=1)
image = cv2.morphologyEx(image, cv2.MORPH_CLOSE, kernel)
image = cv2.medianBlur(image, 3)
return image
img = cv2.imread('2.jpg')
img = cv2.resize(img, None, fx = 0.8, fy = 0.8)
blurImg = noise_remove(img)
hImg, wImg, _ = img.shape
text = pytesseract.image_to_string(blurImg)
print(text)
cv2.waitKey(0)
The output I get:
Result:
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