How to remove the noise in the given image so that

问题:

I have done otsu thresholding on this bengali text image and use tesseract to OCR but the output is very bad. What preprocessing should I apply to remove the noise? I want to deskew the image as well, as it has slight skewed. My code is given below

import tesserocr
from PIL import Image
import cv2
import codecs
image = cv2.imread("crop2.bmp", 0)
(thresh, bw_img) = cv2.threshold(image, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)

img = Image.fromarray(bw_img)
text = tesserocr.image_to_text(img, lang='ben')
file = codecs.open("output_text", "w", "utf-8")
file.write(text)
file.close()

回答1:

You can remove the noises by removing small connected components that might improve the accuracy. You would also need to get optimum value for noisy components threshold value.

import cv2 
import numpy as np

img = cv2.imread(r'D:\Image\st5.png',0)
ret, bw = cv2.threshold(img, 128,255,cv2.THRESH_BINARY_INV)

connectivity = 4
nb_components, output, stats, centroids = cv2.connectedComponentsWithStats(bw, connectivity, cv2.CV_32S)
sizes = stats[1:, -1]; nb_components = nb_components - 1
min_size = 50 #threshhold value for small noisy components
img2 = np.zeros((output.shape), np.uint8)

for i in range(0, nb_components):
    if sizes[i] >= min_size:
        img2[output == i + 1] = 255

res = cv2.bitwise_not(img2)

Denoised image: