Cleaning up captcha image

Here is a C# solution using OpenCvSharp (which should be easy to convert back to python/c++ because the method names are exactly the same).

It uses OpenCV's inpainting technique to avoid destroying too much of the letters before possibly running an OCR phase. We can see that the lines have a different color than the rest, so we'll use that information very early, before any grayscaling/blackwhiting. Steps are as follow:

• build a mask from the lines using their color (#707070)
• dilate that mask a bit because the lines may have been drawn with antialiasing
• repaint ("inpaint") the original image using this mask, which will remove the lines while preserving most of what was below the lines (letters). Note we could remove the small points before that step, I think it would be even better
• apply some dilate/blur/threshold to finalize

Here is the mask:

Here is the result:

Here is the result on sample set:

Here is the C# code:

static void Decaptcha(string filePath)
{
    // load the file
    using (var src = new Mat(filePath))
    {
        using (var binaryMask = new Mat())
        {
            // lines color is different than text
            var linesColor = Scalar.FromRgb(0x70, 0x70, 0x70);

            // build a mask of lines
            Cv2.InRange(src, linesColor, linesColor, binaryMask);
            using (var masked = new Mat())
            {
                // build the corresponding image
                // dilate lines a bit because aliasing may have filtered borders too much during masking
                src.CopyTo(masked, binaryMask);
                int linesDilate = 3;
                using (var element = Cv2.GetStructuringElement(MorphShapes.Ellipse, new Size(linesDilate, linesDilate)))
                {
                    Cv2.Dilate(masked, masked, element);
                }

                // convert mask to grayscale
                Cv2.CvtColor(masked, masked, ColorConversionCodes.BGR2GRAY);
                using (var dst = src.EmptyClone())
                {
                    // repaint big lines
                    Cv2.Inpaint(src, masked, dst, 3, InpaintMethod.NS);

                    // destroy small lines
                    linesDilate = 2;
                    using (var element = Cv2.GetStructuringElement(MorphShapes.Ellipse, new Size(linesDilate, linesDilate)))
                    {
                        Cv2.Dilate(dst, dst, element);
                    }

                    Cv2.GaussianBlur(dst, dst, new Size(5, 5), 0);
                    using (var dst2 = dst.BilateralFilter(5, 75, 75))
                    {
                        // basically make it B&W
                        Cv2.CvtColor(dst2, dst2, ColorConversionCodes.BGR2GRAY);
                        Cv2.Threshold(dst2, dst2, 255, 255, ThresholdTypes.Otsu);

                        // save the file
                        dst2.SaveImage(Path.Combine(
                            Path.GetDirectoryName(filePath),
                            Path.GetFileNameWithoutExtension(filePath) + "_dst" + Path.GetExtension(filePath)));
                    }
                }
            }
        }
    }
}

Take a closer look to your captcha. most of the dust in that image has a different grayscale value than the text.

The text is in 140 and the dust is in 112.

A simple grayscale filtering will help a lot here.

from scipy.misc import imread, imsave
import numpy as np

infile = "A1nO4.png"
outfile = "A1nO4_out.png"

im = imread(infile, True)
out_im = np.ones(im.shape) * 255

out_im[im == 140] = 0

imsave(outfile, out_im)

Now use cv2.dilate (cv2.erode on a white on black text) to get rid of the remaining dust.