clean_captcha_image.py

"""
This script removes stray lines from images using image processing techniques with OpenCV library.

All credit where it's due - https://stackoverflow.com/a/45563349/4411757. Simon Mourier created a script in C# which I
have ported to python. Tested with python 3.5 and opencv-python==3.4.2.17. Shoot your suggestions/improvements in the
comments. Cheers! 
"""

def clean_image(img):
    height, width = img.shape[:2]

    # Specify the color range of the lines you want to remove [lower, upper]
    lower = [0, 0, 0]
    upper = [120, 130, 130]
    lower = np.array(lower, dtype = "uint8")
    upper = np.array(upper, dtype = "uint8") 

    # Create a mask of the lines
    mask = cv2.inRange(img, lower, upper)

    output = cv2.bitwise_and(img, img, mask = mask)

    # As the original comment explains, dilate lines a bit because aliasing 
    # may have filtered borders too much during masking 
    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
    dilation = cv2.dilate(output, kernel, iterations = 3)

    # Conver the mask to gray scale
    gray = cv2.cvtColor(dilation, cv2.COLOR_BGR2GRAY)

    # Reference: https://docs.opencv.org/trunk/df/d3d/tutorial_py_inpainting.html
    # Apply the mask created above on the image
    dst = cv2.inpaint(img,gray,3,cv2.INPAINT_TELEA)


    # Post mask application, there will be inconsistency/gaps/separation of individual 
    # digits/alphabets. So we dilate (puff up the white blobs) so that each individual 
    # digit gets properly connected and considered as one blob (which can be further used
    # to find contours)
    dilation = cv2.dilate(dst, kernel, iterations = 2)

    # Reference for blurring and bilateral filtering: 
    # https://docs.opencv.org/3.1.0/d4/d13/tutorial_py_filtering.html
    blur = cv2.GaussianBlur(dilation,(5,5),0)
    bilateral = cv2.bilateralFilter(blur,5,75,75)
    gray = cv2.cvtColor(bilateral, cv2.COLOR_BGR2GRAY)

    # If pixel value is greater than a threshold value, it is assigned one value (may be white), 
    # else it is assigned another value (may be black)
    # Reference: https://docs.opencv.org/3.4.0/d7/d4d/tutorial_py_thresholding.html
    thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_OTSU)[1]

    return thresh

# Read the image using cv2.imread() and pass it to the clean_image function

# if __name__ == '__main__':
#     img = cv2.imread("<path to captcha image>")
#     img = clean_image(img)
#     cv2.imshow("Final Output", img)
#     cv2.waitKey(0)

intermediary_screenshots.png