使用泛洪填充边缘无法正常工作 [英] Filling edges using flood fill not working properly

问题描述

我正在python中使用openCV来检测混凝土中的裂缝.我能够使用Canny边缘检测来检测裂纹.接下来，我需要填充边缘.我使用了openCV的Floodfill操作，但是一些空白被填充，而一些空白没有被填充.左侧的图像是输入图像，而右侧的是充满水的图像.我猜这是因为我的边缘有些断点.我该如何解决? 我的充水代码:

im_th1 = imginput
im_floodfill = im_th1.copy()
# Mask used to flood filling.
# Notice the size needs to be 2 pixels than the image.
h, w = im_th1.shape[:2]
mask = np.zeros((h + 2, w + 2), np.uint8)

# Floodfill from point (0, 0)
cv2.floodFill(im_floodfill, mask, (5, 5), 255);

# Invert floodfilled image
im_floodfill_inv = cv2.bitwise_not(im_floodfill)

# Combine the two images to get the foreground.
im_out = im_th1 | im_floodfill_inv
cv2.imshow("Foreground", im_out)
cv2.waitKey(0)

解决方案

我找到了想要的解决方案.将其发布在这里，因为它可能会被其他人使用.经过互联网上的一些研究后，这仅是建议的两行代码:图像中. /p>

I am using openCV in python to detect cracks in concrete. I am able to use canny edge detection to detect cracks. Next, I need to fill the edges. I used floodfill operation of openCV but some of the gaps are filled whereas some are not filled. The image on the left is the input image whereas that on the right is the floodfilled image. I am guessing this is because my edges have breaks at points. How do i solve this ? My code for floodfilling:

im_th1 = imginput
im_floodfill = im_th1.copy()
# Mask used to flood filling.
# Notice the size needs to be 2 pixels than the image.
h, w = im_th1.shape[:2]
mask = np.zeros((h + 2, w + 2), np.uint8)

# Floodfill from point (0, 0)
cv2.floodFill(im_floodfill, mask, (5, 5), 255);

# Invert floodfilled image
im_floodfill_inv = cv2.bitwise_not(im_floodfill)

# Combine the two images to get the foreground.
im_out = im_th1 | im_floodfill_inv
cv2.imshow("Foreground", im_out)
cv2.waitKey(0)

解决方案

I found the solution to what i was looking for. Posting it here as it might come of use to others. After some research on the internet, it was just 2 lines of codes as suggested in this : How to complete/close a contour in python opencv?

The code that worked for me is :

kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (9, 9))
dilated = cv2.dilate(image, kernel)
eroded=cv2.erode(dilated,kernel)

The result is in the image attached that shows before and after results.

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