Python OpenCV cv2.bitwise_xor() Guide

Python OpenCV is a powerful library for image processing. One of its key functions is cv2.bitwise_xor(). This function performs a bitwise XOR operation on two images or arrays. It is useful for tasks like masking, blending, and more.

What is cv2.bitwise_xor()?

The cv2.bitwise_xor() function computes the bitwise XOR of two arrays. It compares the binary representation of each pixel in the input arrays. The result is a new array where each pixel is the XOR of the corresponding pixels in the input arrays.

This function is often used in image processing for tasks like creating masks, blending images, and detecting differences between images.

Syntax of cv2.bitwise_xor()

The syntax for cv2.bitwise_xor() is simple:

cv2.bitwise_xor(src1, src2, dst=None, mask=None)

Parameters:

• src1: First input array or image.
• src2: Second input array or image.
• dst: Output array of the same size and type as input arrays.
• mask: Optional operation mask.

How to Use cv2.bitwise_xor()

Let's look at an example to understand how cv2.bitwise_xor() works. We will use two binary images and apply the XOR operation.

import cv2
import numpy as np

# Create two binary images
image1 = np.zeros((300, 300), dtype="uint8")
cv2.rectangle(image1, (50, 50), (250, 250), 255, -1)

image2 = np.zeros((300, 300), dtype="uint8")
cv2.circle(image2, (150, 150), 100, 255, -1)

# Apply bitwise XOR
result = cv2.bitwise_xor(image1, image2)

# Display the results
cv2.imshow("Image 1", image1)
cv2.imshow("Image 2", image2)
cv2.imshow("Result", result)
cv2.waitKey(0)
cv2.destroyAllWindows()

In this example, we create two binary images: one with a rectangle and one with a circle. The cv2.bitwise_xor() function is then used to combine these images. The result shows the XOR of the two shapes.

Applications of cv2.bitwise_xor()

The cv2.bitwise_xor() function has many applications in image processing. Here are a few:

• Masking: XOR can be used to create complex masks by combining simpler shapes.
• Blending: XOR can blend two images in a way that highlights differences.
• Difference Detection: XOR can detect differences between two images by highlighting pixels that are different.

For more advanced image processing techniques, you can explore functions like cv2.bitwise_and() or cv2.bitwise_or().

Conclusion

The cv2.bitwise_xor() function is a powerful tool in Python OpenCV. It allows you to perform bitwise XOR operations on images or arrays. This is useful for tasks like masking, blending, and detecting differences.

By understanding how to use cv2.bitwise_xor(), you can enhance your image processing skills. For more advanced techniques, consider exploring other OpenCV functions like cv2.addWeighted().