Bitwise Operations and Masking

To demonstrate these operations let's create some simple images



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import cv2
import numpy as np

# If you're wondering why only two dimensions, well this is a grayscale image, 
# if we doing a colored image, we'd use 
# rectangle = np.zeros((300, 300, 3),np.uint8)

# Making a sqare
square = np.zeros((300, 300), np.uint8)
cv2.rectangle(square, (50, 50), (250, 250), 255, -2)
cv2.imshow("Square", square)
cv2.waitKey(0)

# Making a ellipse
ellipse = np.zeros((300, 300), np.uint8)
cv2.ellipse(ellipse, (150, 150), (150, 150), 30, 0, 180, 255, -1)
cv2.imshow("Ellipse", ellipse)
cv2.waitKey(0)

cv2.destroyAllWindows()

Experimenting with some bitwise operations



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# Shows only where they intersect
And = cv2.bitwise_and(square, ellipse)
cv2.imshow("AND", And)
cv2.waitKey(0)

# Shows where either square or ellipse is 
bitwiseOr = cv2.bitwise_or(square, ellipse)
cv2.imshow("OR", bitwiseOr)
cv2.waitKey(0) 

# Shows where either exist by itself
bitwiseXor = cv2.bitwise_xor(square, ellipse)
cv2.imshow("XOR", bitwiseXor)
cv2.waitKey(0)

# Shows everything that isn't part of the square
bitwiseNot_sq = cv2.bitwise_not(square)
cv2.imshow("NOT - square", bitwiseNot_sq)
cv2.waitKey(0)

### Notice the last operation inverts the image totally

cv2.destroyAllWindows()



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