create new grayscale mask image by merging two other masks in python

Question

I have two masks and the desired mask result as shown below:

2 original masks and the desired result

I want to create a desired mask result by combining the first 2 masks. Howvever, I only want to produce the white regions if they overlap. IF they don't overlap, then the area should remain black. I'm unsure of how to proceed.

At the moment I have imported the image via cv2 and created a third numpy array based on the dimensions of the original image. I then loop through the two masks and have set a condition based on whether the two values (255 or 0) are the same. If they are then I want to store them or set them in the new mask...:

necrosis_mask_observer_1 = cv2.imread(mask1, 0)
necrosis_mask_observer_2 = cv2.imread(mask2, 0)

map = np.empty(necrosis_mask_observer_1.shape)

height, width = map.shape

# do something here?

for i in range(width):
     for j in range(height):

         necrosis_mask_observer_1_sum = necrosis_mask_observer_1[j : (j+1), i : (i+1)].sum()
         necrosis_mask_observer_2_sum = necrosis_mask_observer_2[j : (j+1), i : (i+1)].sum()

         if necrosis_mask_observer_1_sum == necrosis_mask_observer_2_sum:

         #do something here?
         else:
              continue 

Answer 1

You can do that with a bitwise and operation in Python/OpenCV.

Mask1:

Mask2:

import cv2

# read mask 1
mask1 = cv2.imread('mask1.png')

# read mask 2
mask2 = cv2.imread('mask2.png')

# combine mask
mask3 = cv2.bitwise_and(mask1,mask2)

# save result
cv2.imwrite("mask3.png",mask3)

# show result
cv2.imshow('mask3', mask3)
cv2.waitKey(0)

Combined mask: