For this specific captcha , there's quite a simple solution. But, there's no guarantee for this approach to work on other, even very similar captchas – due to the "nature" of captchas as already mentioned in the comments, and in general when dealing with image-processing tasks with limited provided input data.
Read the image as grayscale.
Threshold the image at nearly white cutoff.
Flood fill the "background" with black.
Run pytesseract
with -psm 6
option.
That'd be the whole code:
import cv2
import pytesseract
# Read image as grayscale
img = cv2.imread('FuZEJ.png', cv2.IMREAD_GRAYSCALE)
# Threshold at nearly white cutoff
thr = cv2.threshold(img, 224, 255, cv2.THRESH_BINARY)[1]
# Floodfill "background" with black
ff = cv2.floodFill(thr, None, (0, 0), 0)[1]
# OCR using pytesseract
text = pytesseract.image_to_string(ff, config='--psm 6').replace('\n', '').replace('\f', '')
print(text)
# xwphs
Caveat: I use a special version of Tesseract from the Mannheim University Library .
----------------------------------------
System information
----------------------------------------
Platform: Windows-10-10.0.16299-SP0
Python: 3.9.1
PyCharm: 2021.1.1
OpenCV: 4.5.1
pytesseract: 5.0.0-alpha.20201127
----------------------------------------
I would try a mask:
import cv2
import numpy as np
def process(img): # To process the image
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
_, img_gray = cv2.threshold(img_gray, 224, 255, cv2.THRESH_TOZERO_INV)
img_blur = cv2.GaussianBlur(img_gray, (7, 7), 6)
img_canny = cv2.Canny(img_blur, 0, 100)
return cv2.dilate(img_canny, np.ones((1, 5)), iterations=1)
def get_mask(img): # To generate the mask
mask = np.zeros(img.shape[:2], 'uint8')
contours, _ = cv2.findContours(process(img), cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
for cnt in contours:
cv2.drawContours(mask, [cnt], -1, 255, -1)
return mask
def crop(img, mask): # To mask an image and use white background
bg = np.full(img.shape, 255, 'uint8')
fg = cv2.bitwise_or(img, img, mask=mask)
fg_back_inv = cv2.bitwise_or(bg, bg, mask=cv2.bitwise_not(mask))
return cv2.bitwise_or(fg, fg_back_inv)
img = cv2.imread("image.png")
img = cv2.pyrUp(cv2.pyrUp(img)) # To enlarge image by 4x
cv2.imshow("Masked Image", crop(img, get_mask(img)))
cv2.waitKey(0)
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