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How to count the number of neighbor pixels in a mask?

asked 2014-02-24 01:53:01 -0500

fbr gravatar image
Let's say I have a 0 or 1 mask image.

How can I count, for each pixel, its number of 9-connected
neighbors which are set to 1?

I tried this:

count_neighbors_K = np.array([ [1,1,1],
                               [1,0,1],
                               [1,1,1] ], dtype = np.uint8)


test_array = np.array([ [0,0,0,0],
                        [0,0,0,0],
                        [0,1,0,0],
                        [0,0,0,0] ], dtype = np.uint8)

# neighbors_count = cv2.filter2D(mask, -1, count_neighbors_K)
neighbors_count = cv2.filter2D(test_array, -1, count_neighbors_K)
neighbors_count

But the count on the borders are wrong:

>>> neighbors_count
array([[0, 0, 0, 0],
       [2, 1, 1, 0],
       [2, 0, 1, 0],
       [4, 2, 2, 0]], dtype=uint8)
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answered 2014-02-24 02:55:36 -0500

Nghia gravatar image

The default border handling scheme is reflection (BORDER_REFLECT_101). You want to pass borderType = BORDER_CONSTANT. But for some reason filter2D doesn't let you specify the constant colour to use according to the doc. So not sure if it'll work. In the worse case you can make a slightly larger image, pad the borders with zeros, run the function and get the subimage.

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Asked: 2014-02-24 01:53:01 -0500

Seen: 759 times

Last updated: Feb 24 '14