[SOLVED] Finding holes in a binary image

Finding holes in a binary image

Assume we have following binary image

0 represents background pixels and 1 represents image pixels.As you can see there are two holes in this image.Is there a way to obtain the number of holes in this image using algorithms?(Java or Python but not Matlab)

Solution

Here is some idea presented as code (and it might be not what you need).

The problem is, that i don't understand your example. Depending on the neighborhood-definition, there are different results possible.

If you have a 8-neighborhood, all zeros are connected somehow (what does that mean about the surrounding 1's?).
If you have a 4-neighborhood, each one surrounded by 4 1's represents a new hole
- Of course you could postprocess this but the question is still unclear

Code

import numpy as np
from skimage.measure import label

img = np.array([[0,0,1,0],
                [0,1,0,1],
                [0,1,0,1],
                [0,0,1,0],
                [0,1,0,0],
                [1,0,1,0],
                [0,1,0,0],
                [0,0,0,0]])

labels = label(img, connectivity=1, background=-1)  # conn=1 -> 4 neighbors
label_vals = np.unique(labels)                      # conn=2 -> 8 neighbors

counter = 0
for i in label_vals:
    indices = np.where(labels == i)
    if indices:
        if img[indices][0] == 0:
            print('hole: ', indices)
            counter += 1


print(img)
print(labels)
print(counter)

Output

('hole: ', (array([0, 0, 1, 2, 3, 3, 4]), array([0, 1, 0, 0, 0, 1, 0])))
('hole: ', (array([0]), array([3])))
('hole: ', (array([1, 2]), array([2, 2])))
('hole: ', (array([3, 4, 4, 5, 6, 6, 6, 7, 7, 7, 7]), array([3, 2, 3, 3, 0, 2, 3, 0, 1, 2, 3])))
('hole: ', (array([5]), array([1])))
[[0 0 1 0]
 [0 1 0 1]
 [0 1 0 1]
 [0 0 1 0]
 [0 1 0 0]
 [1 0 1 0]
 [0 1 0 0]
 [0 0 0 0]]
[[ 1  1  2  3]
 [ 1  4  5  6]
 [ 1  4  5  6]
 [ 1  1  7  8]
 [ 1  9  8  8]
 [10 11 12  8]
 [ 8 13  8  8]
 [ 8  8  8  8]]
5