How to remove unclosed curves in a binary image? - opencv

Question

After some processing, I have this binary image:
I want to remove the unclosed curves i.e. the top left and the bottom right curves. Can you suggest me the algorithm for doing this? Thanks.

Answer 1

As #John Zwinck mentions this can be done using floodfill, but I figure your problem is you want to return to the original black background, and retain the contours of the closed shapes. While you could use contours to figure this out, here is a fairly simple approach that will remove all non-closed and unenclosed line segments from an image, even if they are attached to a closed shape, But retain the edges of the closed curves.
floodfill image with white - this removes your problem non-closed lines, but also the borders of your wanted objects.
erode the image, then invert it
AND the image with the original image - thus restoring the borders.
Output:
The code is in python, but should easily translate to the usual C++ cv2 usage.
import cv2
import numpy as np
im = cv2.imread('I7qZP.png',cv2.CV_LOAD_IMAGE_GRAYSCALE)
im2 = im.copy()
mask = np.zeros((np.array(im.shape)+2), np.uint8)
cv2.floodFill(im, mask, (0,0), (255))
im = cv2.erode(im, np.ones((3,3)))
im = cv2.bitwise_not(im)
im = cv2.bitwise_and(im,im2)
cv2.imshow('show', im)
cv2.imwrite('fin.png',im)
cv2.waitKey()

Answer 2

You're looking for Flood Fill: http://en.wikipedia.org/wiki/Flood_fill

Answer 3

I had a bit of a play with an idea, though it wouldn't be the most efficient method by a long shot. I converted the image to an array of 300x300 chars, and it seemed to work well on that. I'm not familiar with opencv.
The idea was go through each pixel and see if it marks the end of a line - if so make that pixel black. Repeat until there are no changes to the picture.
The criteria I used to identify a pixel as the end of a line was to note the number of black-white changes around the loop of that pixel. If there are less than 4 changes it is the end of a line. This won't work if the lines are thicker than 1 px. I could probably come up with something better. It seemed to work with the provided picture.
do {
res = 0;
for (i = 1; i < 299; i++) {
for (j = 1; j < 299; j++) {
if (image[i][j] != 0) {
count = 0;
if (image[i-1][j-1] != image[i-1][j+0]) count++;
if (image[i-1][j+0] != image[i-1][j+1]) count++;
if (image[i-1][j+1] != image[i+0][j+1]) count++;
if (image[i+0][j+1] != image[i+1][j+1]) count++;
if (image[i+1][j+1] != image[i+1][j+0]) count++;
if (image[i+1][j+0] != image[i+1][j-1]) count++;
if (image[i+1][j-1] != image[i+0][j-1]) count++;
if (image[i+0][j-1] != image[i-1][j-1]) count++;
if (count < 4) {
image[i][j] = 0;
res = 1;
}
}
}
}
} while (res);